Renaming examples in apex-pdp

Renaming the examples as per what the documentation expects them.
Otherwise the documents won't work.

Change-Id: Ib9e30bf5a4cec0fec981372e1d9f3a0ee5d60f2f
Issue-ID: POLICY-861
Signed-off-by: ramverma <ram.krishna.verma@ericsson.com>

32 files changed, 0 insertions, 13195 deletions

diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java
deleted file mode 100644
index f574c74ec..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java
+++ /dev/null
@@ -1,243 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive.concepts;
-
-import java.io.Serializable;
-import java.util.ArrayList;
-import java.util.LinkedList;
-import java.util.List;
-
-/**
- * The Class AnomalyDetection is used as a Java context for Adaptive anomaly detection in the adaptive domain.
- */
-public class AnomalyDetection implements Serializable {
-    private static final long serialVersionUID = -823013127095523727L;
-
-    private static final int HASH_PRIME_1 = 31;
-    private static final int HASH_PRIME_2 = 1231;
-    private static final int HASH_PRIME_3 = 1237;
-
-    private boolean firstRound = true;
-    private int frequency = 0;
-
-    /**
-     * The Constructor creates an AnomalyDetection instance.
-     */
-    public AnomalyDetection() {
-        firstRound = true;
-        frequency = 0;
-    }
-
-    private List<Double> anomalyScores = new LinkedList<>();
-    private List<Double> frequencyForecasted;
-
-    /**
-     * Checks if the AnomalyDetection instance is initialized.
-     *
-     * @return true, if the AnomalyDetection instance is initialized
-     */
-    public boolean isInitialized() {
-        return (frequencyForecasted != null);
-    }
-
-    /**
-     * Initializes the AnomalyDetection instance.
-     *
-     * @param incomingFrequency the frequency
-     */
-    public void init(final int incomingFrequency) {
-        frequencyForecasted = new ArrayList<>(incomingFrequency);
-        for (int i = 0; i < incomingFrequency; i++) {
-            frequencyForecasted.add(null);
-        }
-    }
-
-    /**
-     * Indicates if this is the first round of the algorithm.
-     *
-     * @return true if this is the first round of the algorithm
-     */
-    public boolean getFirstRound() {
-        return firstRound;
-    }
-
-    /**
-     * Sets the first round indicator of the algorithm.
-     *
-     * @param firstRound the first round indicator of the algorithm
-     */
-    public void setFirstRound(final boolean firstRound) {
-        this.firstRound = firstRound;
-    }
-
-    /**
-     * Gets the frequency value of the algorithm.
-     *
-     * @return the frequency value of the algorithm
-     */
-    public int getFrequency() {
-        return frequency;
-    }
-
-    /**
-     * Sets the frequency value of the algorithm.
-     *
-     * @param frequency the frequency value of the algorithm
-     */
-    public void setFrequency(final int frequency) {
-        this.frequency = frequency;
-    }
-
-    /**
-     * Gets the anomaly score values of the algorithm.
-     *
-     * @return the anomaly score values of the algorithm
-     */
-    public List<Double> getAnomalyScores() {
-        return anomalyScores;
-    }
-
-    /**
-     * Sets the anomaly score values of the algorithm.
-     *
-     * @param anomalyScores the anomaly score values of the algorithm
-     */
-    public void setAnomalyScores(final LinkedList<Double> anomalyScores) {
-        this.anomalyScores = anomalyScores;
-    }
-
-    /**
-     * Check if the anomaly score values of the algorithm are set.
-     *
-     * @return true, if the anomaly score values of the algorithm are set
-     */
-    public boolean checkSetAnomalyScores() {
-        return ((anomalyScores != null) && (!anomalyScores.isEmpty()));
-    }
-
-    /**
-     * Unset the anomaly score values of the algorithm.
-     */
-    public void unsetAnomalyScores() {
-        anomalyScores = null;
-    }
-
-    /**
-     * Gets the frequency forecasted by the algorithm.
-     *
-     * @return the frequency forecasted by the algorithm
-     */
-    public List<Double> getFrequencyForecasted() {
-        return frequencyForecasted;
-    }
-
-    /**
-     * Sets the frequency forecasted by the algorithm.
-     *
-     * @param frequencyForecasted the frequency forecasted by the algorithm
-     */
-    public void setFrequencyForecasted(final List<Double> frequencyForecasted) {
-        this.frequencyForecasted = frequencyForecasted;
-    }
-
-    /**
-     * Check if the frequency forecasted by the algorithm is set.
-     *
-     * @return true, if the frequency forecasted by the algorithm is set
-     */
-    public boolean checkSetFrequencyForecasted() {
-        return ((frequencyForecasted != null) && (!frequencyForecasted.isEmpty()));
-    }
-
-    /**
-     * Unset the frequency forecasted by the algorithm.
-     */
-    public void unsetFrequencyForecasted() {
-        frequencyForecasted = null;
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see java.lang.Object#toString()
-     */
-    @Override
-    public String toString() {
-        return "AnomalyDetection [firstRound=" + firstRound + ", frequency=" + frequency + ", anomalyScores="
-                + anomalyScores + ", frequencyForecasted=" + frequencyForecasted + "]";
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see java.lang.Object#hashCode()
-     */
-    @Override
-    public int hashCode() {
-        final int prime = HASH_PRIME_1;
-        int result = 1;
-        result = prime * result + ((anomalyScores == null) ? 0 : anomalyScores.hashCode());
-        result = prime * result + (firstRound ? HASH_PRIME_2 : HASH_PRIME_3);
-        result = prime * result + frequency;
-        result = prime * result + ((frequencyForecasted == null) ? 0 : frequencyForecasted.hashCode());
-        return result;
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see java.lang.Object#equals(java.lang.Object)
-     */
-    @Override
-    public boolean equals(final Object obj) {
-        if (this == obj) {
-            return true;
-        }
-        if (obj == null) {
-            return false;
-        }
-        if (getClass() != obj.getClass()) {
-            return false;
-        }
-        final AnomalyDetection other = (AnomalyDetection) obj;
-        if (anomalyScores == null) {
-            if (other.anomalyScores != null) {
-                return false;
-            }
-        } else if (!anomalyScores.equals(other.anomalyScores)) {
-            return false;
-        }
-        if (firstRound != other.firstRound) {
-            return false;
-        }
-        if (frequency != other.frequency) {
-            return false;
-        }
-        if (frequencyForecasted == null) {
-            if (other.frequencyForecasted != null) {
-                return false;
-            }
-        } else if (!frequencyForecasted.equals(other.frequencyForecasted)) {
-            return false;
-        }
-        return true;
-    }
-}
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java
deleted file mode 100644
index f2e27725b..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java
+++ /dev/null
@@ -1,198 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive.concepts;
-
-import java.io.Serializable;
-import java.util.ArrayList;
-import java.util.List;
-
-/**
- * The Class AutoLearn is used as a Java context for Adaptive auto-learning of trends towards a fixed value in the
- * adaptive domain.
- */
-public class AutoLearn implements Serializable {
-    private static final long serialVersionUID = 3825970380434170754L;
-
-    private List<Double> avDiffs = null;
-
-    private List<Long> counts = null;
-
-    /**
-     * The Constructor creates an AutoLearn concept.
-     */
-    public AutoLearn() {}
-
-    /**
-     * Checks if the Autolearn instance is initialized.
-     *
-     * @return true, if the Autolearn instance is initialized
-     */
-    public boolean isInitialized() {
-        return (avDiffs != null && counts != null);
-    }
-
-    /**
-     * initializes the auto learning algorithm with the number of convergent variables to use.
-     *
-     * @param size the number of convergent variables to use
-     */
-    public void init(final int size) {
-        if (avDiffs == null || avDiffs.size() == 0) {
-            avDiffs = new ArrayList<>(size);
-            for (int i = 0; i < size; i++) {
-                avDiffs.add(i, Double.NaN);
-            }
-        }
-
-        if (counts == null || counts.size() == 0) {
-            counts = new ArrayList<>(size);
-            for (int i = 0; i < size; i++) {
-                counts.add(i, 0L);
-            }
-        }
-    }
-
-    /**
-     * Gets the average difference values of the algorithm.
-     *
-     * @return the average difference values of the algorithm
-     */
-    public List<Double> getAvDiffs() {
-        return avDiffs;
-    }
-
-    /**
-     * Sets the average difference values of the algorithm.
-     *
-     * @param avDiffs the average difference values of the algorithm
-     */
-    public void setAvDiffs(final List<Double> avDiffs) {
-        this.avDiffs = avDiffs;
-    }
-
-    /**
-     * Check if the average difference values of the algorithm are set.
-     *
-     * @return true, if check set av diffs
-     */
-    public boolean checkSetAvDiffs() {
-        return ((avDiffs != null) && (!avDiffs.isEmpty()));
-    }
-
-    /**
-     * Unset the average difference values of the algorithm.
-     */
-    public void unsetAvDiffs() {
-        avDiffs = null;
-    }
-
-    /**
-     * Gets the count values of the algorithm.
-     *
-     * @return the count values of the algorithm
-     */
-    public List<Long> getCounts() {
-        return counts;
-    }
-
-    /**
-     * Sets the count values of the algorithm.
-     *
-     * @param counts the count values of the algorithm
-     */
-    public void setCounts(final List<Long> counts) {
-        this.counts = counts;
-    }
-
-    /**
-     * Check if the count values of the algorithm are set.
-     *
-     * @return true, if the count values of the algorithm are set
-     */
-    public boolean checkSetCounts() {
-        return ((counts != null) && (!counts.isEmpty()));
-    }
-
-    /**
-     * Unset the count values of the algorithm.
-     */
-    public void unsetCounts() {
-        counts = null;
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see java.lang.Object#toString()
-     */
-    @Override
-    public String toString() {
-        return "AutoLearn [avDiffs=" + avDiffs + ", counts=" + counts + "]";
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see java.lang.Object#hashCode()
-     */
-    @Override
-    public int hashCode() {
-        final int prime = 31;
-        int result = 1;
-        result = prime * result + ((avDiffs == null) ? 0 : avDiffs.hashCode());
-        result = prime * result + ((counts == null) ? 0 : counts.hashCode());
-        return result;
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see java.lang.Object#equals(java.lang.Object)
-     */
-    @Override
-    public boolean equals(final Object obj) {
-        if (this == obj) {
-            return true;
-        }
-        if (obj == null) {
-            return false;
-        }
-        if (getClass() != obj.getClass()) {
-            return false;
-        }
-        final AutoLearn other = (AutoLearn) obj;
-        if (avDiffs == null) {
-            if (other.avDiffs != null) {
-                return false;
-            }
-        } else if (!avDiffs.equals(other.avDiffs)) {
-            return false;
-        }
-        if (counts == null) {
-            if (other.counts != null) {
-                return false;
-            }
-        } else if (!counts.equals(other.counts)) {
-            return false;
-        }
-        return true;
-    }
-}
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/package-info.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/package-info.java
deleted file mode 100644
index 8561ed074..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/package-info.java
+++ /dev/null
@@ -1,27 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-/**
- * Provides Java types that are used in the Adaptive domain.
- *
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-
-package org.onap.policy.apex.examples.adaptive.concepts;
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelFactory.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelFactory.java
deleted file mode 100644
index 6242b1618..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelFactory.java
+++ /dev/null
@@ -1,558 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive.model;
-
-import org.onap.policy.apex.model.basicmodel.concepts.ApexRuntimeException;
-import org.onap.policy.apex.model.basicmodel.concepts.AxArtifactKey;
-import org.onap.policy.apex.model.basicmodel.concepts.AxKeyInformation;
-import org.onap.policy.apex.model.basicmodel.concepts.AxReferenceKey;
-import org.onap.policy.apex.model.basicmodel.concepts.AxValidationResult;
-import org.onap.policy.apex.model.contextmodel.concepts.AxContextAlbum;
-import org.onap.policy.apex.model.contextmodel.concepts.AxContextAlbums;
-import org.onap.policy.apex.model.contextmodel.concepts.AxContextSchema;
-import org.onap.policy.apex.model.contextmodel.concepts.AxContextSchemas;
-import org.onap.policy.apex.model.eventmodel.concepts.AxEvent;
-import org.onap.policy.apex.model.eventmodel.concepts.AxEvents;
-import org.onap.policy.apex.model.eventmodel.concepts.AxField;
-import org.onap.policy.apex.model.policymodel.concepts.AxLogicReader;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicies;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicy;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-import org.onap.policy.apex.model.policymodel.concepts.AxState;
-import org.onap.policy.apex.model.policymodel.concepts.AxStateOutput;
-import org.onap.policy.apex.model.policymodel.concepts.AxStateTaskOutputType;
-import org.onap.policy.apex.model.policymodel.concepts.AxStateTaskReference;
-import org.onap.policy.apex.model.policymodel.concepts.AxTask;
-import org.onap.policy.apex.model.policymodel.concepts.AxTaskLogic;
-import org.onap.policy.apex.model.policymodel.concepts.AxTaskSelectionLogic;
-import org.onap.policy.apex.model.policymodel.concepts.AxTasks;
-import org.onap.policy.apex.model.policymodel.handling.PolicyLogicReader;
-
-/**
- * The Class AdaptiveDomainModelFactory.
- */
-public class AdaptiveDomainModelFactory {
-
-    /**
-     * Gets the anomaly detection policy model.
-     *
-     * @return the anomaly detection policy model
-     */
-    // CHECKSTYLE:OFF: checkstyle:maximumMethodLength
-    public AxPolicyModel getAnomalyDetectionPolicyModel() {
-        // CHECKSTYLE:ON: checkstyle:maximumMethodLength
-        // Data types for event parameters
-        final AxContextSchema monitoredValue =
-                new AxContextSchema(new AxArtifactKey("MonitoredValue", "0.0.1"), "Java", "java.lang.Double");
-        final AxContextSchema iteration =
-                new AxContextSchema(new AxArtifactKey("Iteration", "0.0.1"), "Java", "java.lang.Integer");
-
-        final AxContextSchemas adContextSchemas = new AxContextSchemas(new AxArtifactKey("AADMDatatypes", "0.0.1"));
-        adContextSchemas.getSchemasMap().put(monitoredValue.getKey(), monitoredValue);
-        adContextSchemas.getSchemasMap().put(iteration.getKey(), iteration);
-
-        final AxEvent anomalyDetectionTriggerEvent =
-                new AxEvent(new AxArtifactKey("AnomalyDetectionTriggerEvent", "0.0.1"),
-                        "org.onap.policy.apex.examples.adaptive.events");
-        anomalyDetectionTriggerEvent.setSource("External");
-        anomalyDetectionTriggerEvent.setTarget("Match");
-        anomalyDetectionTriggerEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(anomalyDetectionTriggerEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        anomalyDetectionTriggerEvent.getParameterMap().put("Iteration", new AxField(
-                new AxReferenceKey(anomalyDetectionTriggerEvent.getKey(), "Iteration"), iteration.getKey()));
-
-        final AxEvent anomalyDetectionMatchEvent = new AxEvent(new AxArtifactKey("AnomalyDetectionMatchEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        anomalyDetectionMatchEvent.setSource("Match");
-        anomalyDetectionMatchEvent.setTarget("Establish");
-        anomalyDetectionMatchEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(anomalyDetectionMatchEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        anomalyDetectionMatchEvent.getParameterMap().put("Iteration",
-                new AxField(new AxReferenceKey(anomalyDetectionMatchEvent.getKey(), "Iteration"), iteration.getKey()));
-
-        final AxEvent anomalyDetectionEstablishEvent =
-                new AxEvent(new AxArtifactKey("AnomalyDetectionEstablishEvent", "0.0.1"),
-                        "org.onap.policy.apex.examples.adaptive.events");
-        anomalyDetectionEstablishEvent.setSource("Establish");
-        anomalyDetectionEstablishEvent.setTarget("Decide");
-        anomalyDetectionEstablishEvent.getParameterMap().put("MonitoredValue",
-                new AxField(new AxReferenceKey(anomalyDetectionEstablishEvent.getKey(), "MonitoredValue"),
-                        monitoredValue.getKey()));
-        anomalyDetectionEstablishEvent.getParameterMap().put("Iteration", new AxField(
-                new AxReferenceKey(anomalyDetectionEstablishEvent.getKey(), "Iteration"), iteration.getKey()));
-
-        final AxEvent anomalyDetectionDecideEvent =
-                new AxEvent(new AxArtifactKey("AnomalyDetectionDecideEvent", "0.0.1"),
-                        "org.onap.policy.apex.examples.adaptive.events");
-        anomalyDetectionDecideEvent.setSource("Decide");
-        anomalyDetectionDecideEvent.setTarget("Act");
-        anomalyDetectionDecideEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(anomalyDetectionDecideEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        anomalyDetectionDecideEvent.getParameterMap().put("Iteration",
-                new AxField(new AxReferenceKey(anomalyDetectionDecideEvent.getKey(), "Iteration"), iteration.getKey()));
-
-        final AxEvent anomalyDetectionActEvent = new AxEvent(new AxArtifactKey("AnomalyDetectionActEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        anomalyDetectionActEvent.setSource("Act");
-        anomalyDetectionActEvent.setTarget("External");
-        anomalyDetectionActEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(anomalyDetectionActEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        anomalyDetectionActEvent.getParameterMap().put("Iteration",
-                new AxField(new AxReferenceKey(anomalyDetectionActEvent.getKey(), "Iteration"), iteration.getKey()));
-
-        final AxEvents anomalyDetectionEvents = new AxEvents(new AxArtifactKey("AnomalyDetectionEvents", "0.0.1"));
-        anomalyDetectionEvents.getEventMap().put(anomalyDetectionTriggerEvent.getKey(), anomalyDetectionTriggerEvent);
-        anomalyDetectionEvents.getEventMap().put(anomalyDetectionMatchEvent.getKey(), anomalyDetectionMatchEvent);
-        anomalyDetectionEvents.getEventMap().put(anomalyDetectionEstablishEvent.getKey(),
-                anomalyDetectionEstablishEvent);
-        anomalyDetectionEvents.getEventMap().put(anomalyDetectionDecideEvent.getKey(), anomalyDetectionDecideEvent);
-        anomalyDetectionEvents.getEventMap().put(anomalyDetectionActEvent.getKey(), anomalyDetectionActEvent);
-
-        // Data types for context
-        final AxContextSchema anomalyDetection = new AxContextSchema(new AxArtifactKey("AnomalyDetection", "0.0.1"),
-                "Java", "org.onap.policy.apex.examples.adaptive.concepts.AnomalyDetection");
-        adContextSchemas.getSchemasMap().put(anomalyDetection.getKey(), anomalyDetection);
-
-        // One context map
-        final AxContextAlbum anomalyDetectionAlbum = new AxContextAlbum(
-                new AxArtifactKey("AnomalyDetectionAlbum", "0.0.1"), "APPLICATION", true, anomalyDetection.getKey());
-        final AxContextAlbums anomalyDetectionAlbums =
-                new AxContextAlbums(new AxArtifactKey("AnomalyDetectionAlbums", "0.0.1"));
-        anomalyDetectionAlbums.getAlbumsMap().put(anomalyDetectionAlbum.getKey(), anomalyDetectionAlbum);
-
-        // Tasks
-        final AxLogicReader logicReader =
-                new PolicyLogicReader().setLogicPackage(this.getClass().getPackage().getName())
-                        .setDefaultLogic("DefaultAnomalyDetectionTask_Logic");
-
-        final AxTask anomalyDetectionMatchTask = new AxTask(new AxArtifactKey("AnomalyDetectionMatchTask", "0.0.1"));
-        anomalyDetectionMatchTask.duplicateInputFields(anomalyDetectionTriggerEvent.getParameterMap());
-        anomalyDetectionMatchTask.duplicateOutputFields(anomalyDetectionMatchEvent.getParameterMap());
-        anomalyDetectionMatchTask
-                .setTaskLogic(new AxTaskLogic(anomalyDetectionMatchTask.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask anomalyDetectionEstablishTask =
-                new AxTask(new AxArtifactKey("AnomalyDetectionEstablishTask", "0.0.1"));
-        anomalyDetectionEstablishTask.duplicateInputFields(anomalyDetectionMatchEvent.getParameterMap());
-        anomalyDetectionEstablishTask.duplicateOutputFields(anomalyDetectionEstablishEvent.getParameterMap());
-        anomalyDetectionEstablishTask.setTaskLogic(
-                new AxTaskLogic(anomalyDetectionEstablishTask.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask anomalyDetectionDecideTask0 =
-                new AxTask(new AxArtifactKey("AnomalyDetectionDecideTask0", "0.0.1"));
-        anomalyDetectionDecideTask0.duplicateInputFields(anomalyDetectionEstablishEvent.getParameterMap());
-        anomalyDetectionDecideTask0.duplicateOutputFields(anomalyDetectionDecideEvent.getParameterMap());
-        anomalyDetectionDecideTask0
-                .setTaskLogic(new AxTaskLogic(anomalyDetectionDecideTask0.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask anomalyDetectionDecideTask1 =
-                new AxTask(new AxArtifactKey("AnomalyDetectionDecideTask1", "0.0.1"));
-        anomalyDetectionDecideTask1.duplicateInputFields(anomalyDetectionEstablishEvent.getParameterMap());
-        anomalyDetectionDecideTask1.duplicateOutputFields(anomalyDetectionDecideEvent.getParameterMap());
-        anomalyDetectionDecideTask1
-                .setTaskLogic(new AxTaskLogic(anomalyDetectionDecideTask1.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask anomalyDetectionDecideTask2 =
-                new AxTask(new AxArtifactKey("AnomalyDetectionDecideTask2", "0.0.1"));
-        anomalyDetectionDecideTask2.duplicateInputFields(anomalyDetectionEstablishEvent.getParameterMap());
-        anomalyDetectionDecideTask2.duplicateOutputFields(anomalyDetectionDecideEvent.getParameterMap());
-        anomalyDetectionDecideTask2
-                .setTaskLogic(new AxTaskLogic(anomalyDetectionDecideTask2.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask anomalyDetectionActTask = new AxTask(new AxArtifactKey("AnomalyDetectionActTask", "0.0.1"));
-        anomalyDetectionActTask.duplicateInputFields(anomalyDetectionDecideEvent.getParameterMap());
-        anomalyDetectionActTask.duplicateOutputFields(anomalyDetectionActEvent.getParameterMap());
-        anomalyDetectionActTask
-                .setTaskLogic(new AxTaskLogic(anomalyDetectionActTask.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTasks anomalyDetectionTasks = new AxTasks(new AxArtifactKey("AnomalyDetectionTasks", "0.0.1"));
-        anomalyDetectionTasks.getTaskMap().put(anomalyDetectionMatchTask.getKey(), anomalyDetectionMatchTask);
-        anomalyDetectionTasks.getTaskMap().put(anomalyDetectionEstablishTask.getKey(), anomalyDetectionEstablishTask);
-        anomalyDetectionTasks.getTaskMap().put(anomalyDetectionDecideTask0.getKey(), anomalyDetectionDecideTask0);
-        anomalyDetectionTasks.getTaskMap().put(anomalyDetectionDecideTask1.getKey(), anomalyDetectionDecideTask1);
-        anomalyDetectionTasks.getTaskMap().put(anomalyDetectionDecideTask2.getKey(), anomalyDetectionDecideTask2);
-        anomalyDetectionTasks.getTaskMap().put(anomalyDetectionActTask.getKey(), anomalyDetectionActTask);
-
-        // Policies
-        logicReader.setDefaultLogic("DefaultState_Logic");
-
-        final AxPolicy anomalyDetectionPolicy = new AxPolicy(new AxArtifactKey("AnomalyDetectionPolicy", "0.0.1"));
-        anomalyDetectionPolicy.setTemplate("MEDA");
-
-        final AxState anomalyDetectionActState =
-                new AxState(new AxReferenceKey(anomalyDetectionPolicy.getKey(), "Act"));
-        anomalyDetectionActState.setTrigger(anomalyDetectionDecideEvent.getKey());
-        final AxStateOutput adAct2Out = new AxStateOutput(anomalyDetectionActState.getKey(),
-                AxReferenceKey.getNullKey(), anomalyDetectionActEvent.getKey());
-        anomalyDetectionActState.getStateOutputs().put(adAct2Out.getKey().getLocalName(), adAct2Out);
-        anomalyDetectionActState.setTaskSelectionLogic(
-                new AxTaskSelectionLogic(anomalyDetectionActState.getKey(), "TaskSelectionLogic", "MVEL", logicReader));
-        anomalyDetectionActState.setDefaultTask(anomalyDetectionActTask.getKey());
-        anomalyDetectionActState.getTaskReferences().put(anomalyDetectionActTask.getKey(),
-                new AxStateTaskReference(anomalyDetectionActState.getKey(), anomalyDetectionActTask.getKey(),
-                        AxStateTaskOutputType.DIRECT, adAct2Out.getKey()));
-
-        logicReader.setDefaultLogic(null);
-
-        final AxState anomalyDetectionDecideState =
-                new AxState(new AxReferenceKey(anomalyDetectionPolicy.getKey(), "Decide"));
-        anomalyDetectionDecideState.setTrigger(anomalyDetectionEstablishEvent.getKey());
-        final AxStateOutput adDec2Act = new AxStateOutput(anomalyDetectionDecideState.getKey(),
-                anomalyDetectionActState.getKey(), anomalyDetectionDecideEvent.getKey());
-        anomalyDetectionDecideState.getStateOutputs().put(adDec2Act.getKey().getLocalName(), adDec2Act);
-        anomalyDetectionDecideState.setTaskSelectionLogic(new AxTaskSelectionLogic(anomalyDetectionDecideState.getKey(),
-                "TaskSelectionLogic", "JAVA", logicReader));
-        anomalyDetectionDecideState.setDefaultTask(anomalyDetectionDecideTask0.getKey());
-        anomalyDetectionDecideState.getContextAlbumReferences().add(anomalyDetectionAlbum.getKey());
-        anomalyDetectionDecideState.getTaskReferences().put(anomalyDetectionDecideTask0.getKey(),
-                new AxStateTaskReference(anomalyDetectionDecideState.getKey(), anomalyDetectionDecideTask0.getKey(),
-                        AxStateTaskOutputType.DIRECT, adDec2Act.getKey()));
-        anomalyDetectionDecideState.getTaskReferences().put(anomalyDetectionDecideTask1.getKey(),
-                new AxStateTaskReference(anomalyDetectionDecideState.getKey(), anomalyDetectionDecideTask1.getKey(),
-                        AxStateTaskOutputType.DIRECT, adDec2Act.getKey()));
-        anomalyDetectionDecideState.getTaskReferences().put(anomalyDetectionDecideTask2.getKey(),
-                new AxStateTaskReference(anomalyDetectionDecideState.getKey(), anomalyDetectionDecideTask2.getKey(),
-                        AxStateTaskOutputType.DIRECT, adDec2Act.getKey()));
-
-        logicReader.setDefaultLogic("DefaultState_Logic");
-
-        final AxState anomalyDetectionEstablishState =
-                new AxState(new AxReferenceKey(anomalyDetectionPolicy.getKey(), "Establish"));
-        anomalyDetectionEstablishState.setTrigger(anomalyDetectionMatchEvent.getKey());
-        final AxStateOutput adEst2Dec = new AxStateOutput(anomalyDetectionEstablishState.getKey(),
-                anomalyDetectionDecideState.getKey(), anomalyDetectionEstablishEvent.getKey());
-        anomalyDetectionEstablishState.getStateOutputs().put(adEst2Dec.getKey().getLocalName(), adEst2Dec);
-        anomalyDetectionEstablishState.setTaskSelectionLogic(new AxTaskSelectionLogic(
-                anomalyDetectionEstablishState.getKey(), "TaskSelectionLogic", "MVEL", logicReader));
-        anomalyDetectionEstablishState.setDefaultTask(anomalyDetectionEstablishTask.getKey());
-        anomalyDetectionEstablishState.getTaskReferences().put(anomalyDetectionEstablishTask.getKey(),
-                new AxStateTaskReference(anomalyDetectionEstablishState.getKey(),
-                        anomalyDetectionEstablishTask.getKey(), AxStateTaskOutputType.DIRECT, adEst2Dec.getKey()));
-
-        final AxState anomalyDetectionMatchState =
-                new AxState(new AxReferenceKey(anomalyDetectionPolicy.getKey(), "Match"));
-        anomalyDetectionMatchState.setTrigger(anomalyDetectionTriggerEvent.getKey());
-        final AxStateOutput adMat2Est = new AxStateOutput(anomalyDetectionMatchState.getKey(),
-                anomalyDetectionEstablishState.getKey(), anomalyDetectionMatchEvent.getKey());
-        anomalyDetectionMatchState.getStateOutputs().put(adMat2Est.getKey().getLocalName(), adMat2Est);
-        anomalyDetectionMatchState.setTaskSelectionLogic(new AxTaskSelectionLogic(anomalyDetectionMatchState.getKey(),
-                "TaskSelectionLogic", "MVEL", logicReader));
-        anomalyDetectionMatchState.setDefaultTask(anomalyDetectionMatchTask.getKey());
-        anomalyDetectionMatchState.getTaskReferences().put(anomalyDetectionMatchTask.getKey(),
-                new AxStateTaskReference(anomalyDetectionMatchState.getKey(), anomalyDetectionMatchTask.getKey(),
-                        AxStateTaskOutputType.DIRECT, adMat2Est.getKey()));
-
-        anomalyDetectionPolicy.setFirstState(anomalyDetectionMatchState.getKey().getLocalName());
-        anomalyDetectionPolicy.getStateMap().put(anomalyDetectionMatchState.getKey().getLocalName(),
-                anomalyDetectionMatchState);
-        anomalyDetectionPolicy.getStateMap().put(anomalyDetectionEstablishState.getKey().getLocalName(),
-                anomalyDetectionEstablishState);
-        anomalyDetectionPolicy.getStateMap().put(anomalyDetectionDecideState.getKey().getLocalName(),
-                anomalyDetectionDecideState);
-        anomalyDetectionPolicy.getStateMap().put(anomalyDetectionActState.getKey().getLocalName(),
-                anomalyDetectionActState);
-
-        final AxPolicies anomalyDetectionPolicies =
-                new AxPolicies(new AxArtifactKey("AnomalyDetectionPolicies", "0.0.1"));
-        anomalyDetectionPolicies.getPolicyMap().put(anomalyDetectionPolicy.getKey(), anomalyDetectionPolicy);
-
-        final AxKeyInformation keyInformation =
-                new AxKeyInformation(new AxArtifactKey("AnomalyDetectionKeyInformation", "0.0.1"));
-        final AxPolicyModel anomalyDetectionPolicyModel =
-                new AxPolicyModel(new AxArtifactKey("AnomalyDetectionPolicyModel", "0.0.1"));
-        anomalyDetectionPolicyModel.setPolicies(anomalyDetectionPolicies);
-        anomalyDetectionPolicyModel.setEvents(anomalyDetectionEvents);
-        anomalyDetectionPolicyModel.setTasks(anomalyDetectionTasks);
-        anomalyDetectionPolicyModel.setAlbums(anomalyDetectionAlbums);
-        anomalyDetectionPolicyModel.setSchemas(adContextSchemas);
-        anomalyDetectionPolicyModel.setKeyInformation(keyInformation);
-        anomalyDetectionPolicyModel.getKeyInformation().generateKeyInfo(anomalyDetectionPolicyModel);
-
-        final AxValidationResult result = anomalyDetectionPolicyModel.validate(new AxValidationResult());
-        if (!result.getValidationResult().equals(AxValidationResult.ValidationResult.VALID)) {
-            throw new ApexRuntimeException("model " + anomalyDetectionPolicyModel.getID() + " is not valid" + result);
-        }
-        return anomalyDetectionPolicyModel;
-    }
-
-    /**
-     * Gets the auto learn policy model.
-     *
-     * @return the auto learn policy model
-     */
-    // CHECKSTYLE:OFF: checkstyle:maximumMethodLength
-    public AxPolicyModel getAutoLearnPolicyModel() {
-        // CHECKSTYLE:ON: checkstyle:maximumMethodLength
-        // Data types for event parameters
-        final AxContextSchema monitoredValue =
-                new AxContextSchema(new AxArtifactKey("MonitoredValue", "0.0.1"), "Java", "java.lang.Double");
-
-        final AxContextSchemas alContextSchemas = new AxContextSchemas(new AxArtifactKey("ALDatatypes", "0.0.1"));
-        alContextSchemas.getSchemasMap().put(monitoredValue.getKey(), monitoredValue);
-
-        final AxEvent autoLearnTriggerEvent = new AxEvent(new AxArtifactKey("AutoLearnTriggerEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        autoLearnTriggerEvent.setSource("External");
-        autoLearnTriggerEvent.setTarget("Match");
-        autoLearnTriggerEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnTriggerEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        autoLearnTriggerEvent.getParameterMap().put("LastMonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnTriggerEvent.getKey(), "LastMonitoredValue"), monitoredValue.getKey()));
-
-        final AxEvent autoLearnMatchEvent = new AxEvent(new AxArtifactKey("AutoLearnMatchEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        autoLearnMatchEvent.setSource("Match");
-        autoLearnMatchEvent.setTarget("Establish");
-        autoLearnMatchEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnMatchEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        autoLearnMatchEvent.getParameterMap().put("LastMonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnMatchEvent.getKey(), "LastMonitoredValue"), monitoredValue.getKey()));
-
-        final AxEvent autoLearnEstablishEvent = new AxEvent(new AxArtifactKey("AutoLearnEstablishEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        autoLearnEstablishEvent.setSource("Establish");
-        autoLearnEstablishEvent.setTarget("Decide");
-        autoLearnEstablishEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnEstablishEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        autoLearnEstablishEvent.getParameterMap().put("LastMonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnEstablishEvent.getKey(), "LastMonitoredValue"), monitoredValue.getKey()));
-
-        final AxEvent autoLearnDecideEvent = new AxEvent(new AxArtifactKey("AutoLearnDecideEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        autoLearnDecideEvent.setSource("Decide");
-        autoLearnDecideEvent.setTarget("Act");
-        autoLearnDecideEvent.getParameterMap().put("MonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnDecideEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        autoLearnDecideEvent.getParameterMap().put("LastMonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnDecideEvent.getKey(), "LastMonitoredValue"), monitoredValue.getKey()));
-
-        final AxEvent autoLearnActEvent = new AxEvent(new AxArtifactKey("AutoLearnActEvent", "0.0.1"),
-                "org.onap.policy.apex.examples.adaptive.events");
-        autoLearnActEvent.setSource("Act");
-        autoLearnActEvent.setTarget("External");
-        autoLearnActEvent.getParameterMap().put("MonitoredValue",
-                new AxField(new AxReferenceKey(autoLearnActEvent.getKey(), "MonitoredValue"), monitoredValue.getKey()));
-        autoLearnActEvent.getParameterMap().put("LastMonitoredValue", new AxField(
-                new AxReferenceKey(autoLearnActEvent.getKey(), "LastMonitoredValue"), monitoredValue.getKey()));
-
-        final AxEvents autoLearnEvents = new AxEvents(new AxArtifactKey("AutoLearnEvents", "0.0.1"));
-        autoLearnEvents.getEventMap().put(autoLearnTriggerEvent.getKey(), autoLearnTriggerEvent);
-        autoLearnEvents.getEventMap().put(autoLearnMatchEvent.getKey(), autoLearnMatchEvent);
-        autoLearnEvents.getEventMap().put(autoLearnEstablishEvent.getKey(), autoLearnEstablishEvent);
-        autoLearnEvents.getEventMap().put(autoLearnDecideEvent.getKey(), autoLearnDecideEvent);
-        autoLearnEvents.getEventMap().put(autoLearnActEvent.getKey(), autoLearnActEvent);
-
-        // Data types for context
-        final AxContextSchema autoLearn = new AxContextSchema(new AxArtifactKey("AutoLearn", "0.0.1"), "Java",
-                "org.onap.policy.apex.examples.adaptive.concepts.AutoLearn");
-        alContextSchemas.getSchemasMap().put(autoLearn.getKey(), autoLearn);
-
-        // One context map
-        final AxContextAlbum autoLearnAlbum = new AxContextAlbum(new AxArtifactKey("AutoLearnAlbum", "0.0.1"),
-                "APPLICATION", true, autoLearn.getKey());
-
-        final AxContextAlbums autoLearnAlbums = new AxContextAlbums(new AxArtifactKey("AutoLearnContext", "0.0.1"));
-        autoLearnAlbums.getAlbumsMap().put(autoLearnAlbum.getKey(), autoLearnAlbum);
-
-        // Tasks
-        final AxLogicReader logicReader = new PolicyLogicReader()
-                .setLogicPackage(this.getClass().getPackage().getName()).setDefaultLogic("DefaultAutoLearnTask_Logic");
-
-        final AxTask autoLearnMatchTask = new AxTask(new AxArtifactKey("AutoLearnMatchTask", "0.0.1"));
-        autoLearnMatchTask.duplicateInputFields(autoLearnTriggerEvent.getParameterMap());
-        autoLearnMatchTask.duplicateOutputFields(autoLearnMatchEvent.getParameterMap());
-        autoLearnMatchTask.setTaskLogic(new AxTaskLogic(autoLearnMatchTask.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnEstablishTask = new AxTask(new AxArtifactKey("AutoLearnEstablishTask", "0.0.1"));
-        autoLearnEstablishTask.duplicateInputFields(autoLearnMatchEvent.getParameterMap());
-        autoLearnEstablishTask.duplicateOutputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnEstablishTask
-                .setTaskLogic(new AxTaskLogic(autoLearnEstablishTask.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        logicReader.setDefaultLogic(null);
-
-        final AxTask autoLearnDecideTask0 = new AxTask(new AxArtifactKey("AutoLearnDecideTask0", "0.0.1"));
-        autoLearnDecideTask0.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask0.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask0
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask0.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnDecideTask1 = new AxTask(new AxArtifactKey("AutoLearnDecideTask1", "0.0.1"));
-        autoLearnDecideTask1.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask1.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask1
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask1.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnDecideTask2 = new AxTask(new AxArtifactKey("AutoLearnDecideTask2", "0.0.1"));
-        autoLearnDecideTask2.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask2.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask2
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask2.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnDecideTask3 = new AxTask(new AxArtifactKey("AutoLearnDecideTask3", "0.0.1"));
-        autoLearnDecideTask3.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask3.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask3
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask3.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnDecideTask4 = new AxTask(new AxArtifactKey("AutoLearnDecideTask4", "0.0.1"));
-        autoLearnDecideTask4.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask4.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask4
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask4.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnDecideTask5 = new AxTask(new AxArtifactKey("AutoLearnDecideTask5", "0.0.1"));
-        autoLearnDecideTask5.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask5.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask5
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask5.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTask autoLearnDecideTask6 = new AxTask(new AxArtifactKey("AutoLearnDecideTask6", "0.0.1"));
-        autoLearnDecideTask6.duplicateInputFields(autoLearnEstablishEvent.getParameterMap());
-        autoLearnDecideTask6.duplicateOutputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnDecideTask6
-                .setTaskLogic(new AxTaskLogic(autoLearnDecideTask6.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        logicReader.setDefaultLogic("DefaultAutoLearnTask_Logic");
-
-        final AxTask autoLearnActTask = new AxTask(new AxArtifactKey("AutoLearnActTask", "0.0.1"));
-        autoLearnActTask.duplicateInputFields(autoLearnDecideEvent.getParameterMap());
-        autoLearnActTask.duplicateOutputFields(autoLearnActEvent.getParameterMap());
-        autoLearnActTask.setTaskLogic(new AxTaskLogic(autoLearnActTask.getKey(), "TaskLogic", "MVEL", logicReader));
-
-        final AxTasks autoLearnTasks = new AxTasks(new AxArtifactKey("AutoLearnTasks", "0.0.1"));
-        autoLearnTasks.getTaskMap().put(autoLearnMatchTask.getKey(), autoLearnMatchTask);
-        autoLearnTasks.getTaskMap().put(autoLearnEstablishTask.getKey(), autoLearnEstablishTask);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask0.getKey(), autoLearnDecideTask0);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask1.getKey(), autoLearnDecideTask1);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask2.getKey(), autoLearnDecideTask2);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask3.getKey(), autoLearnDecideTask3);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask4.getKey(), autoLearnDecideTask4);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask5.getKey(), autoLearnDecideTask5);
-        autoLearnTasks.getTaskMap().put(autoLearnDecideTask6.getKey(), autoLearnDecideTask6);
-        autoLearnTasks.getTaskMap().put(autoLearnActTask.getKey(), autoLearnActTask);
-
-        // Policies
-        logicReader.setDefaultLogic("DefaultState_Logic");
-
-        final AxPolicy autoLearnPolicy = new AxPolicy(new AxArtifactKey("AutoLearnPolicy", "0.0.1"));
-        autoLearnPolicy.setTemplate("MEDA");
-
-        final AxState autoLearnActState = new AxState(new AxReferenceKey(autoLearnPolicy.getKey(), "Act"));
-        autoLearnActState.setTrigger(autoLearnDecideEvent.getKey());
-        final AxStateOutput alAct2Out =
-                new AxStateOutput(autoLearnActState.getKey(), AxReferenceKey.getNullKey(), autoLearnActEvent.getKey());
-        autoLearnActState.getStateOutputs().put(alAct2Out.getKey().getLocalName(), alAct2Out);
-        autoLearnActState.setTaskSelectionLogic(
-                new AxTaskSelectionLogic(autoLearnActState.getKey(), "TaskSelectionLogic", "MVEL", logicReader));
-        autoLearnActState.setDefaultTask(autoLearnActTask.getKey());
-        autoLearnActState.getTaskReferences().put(autoLearnActTask.getKey(),
-                new AxStateTaskReference(autoLearnActState.getKey(), autoLearnActTask.getKey(),
-                        AxStateTaskOutputType.DIRECT, alAct2Out.getKey()));
-
-        logicReader.setDefaultLogic(null);
-
-        final AxState autoLearnDecideState = new AxState(new AxReferenceKey(autoLearnPolicy.getKey(), "Decide"));
-        autoLearnDecideState.setTrigger(autoLearnEstablishEvent.getKey());
-        final AxStateOutput alDec2Act = new AxStateOutput(autoLearnDecideState.getKey(), autoLearnActState.getKey(),
-                autoLearnDecideEvent.getKey());
-        autoLearnDecideState.getStateOutputs().put(alDec2Act.getKey().getLocalName(), alDec2Act);
-        autoLearnDecideState.getContextAlbumReferences().add(autoLearnAlbum.getKey());
-        autoLearnDecideState.setTaskSelectionLogic(
-                new AxTaskSelectionLogic(autoLearnDecideState.getKey(), "TaskSelectionLogic", "JAVA", logicReader));
-        autoLearnDecideState.setDefaultTask(autoLearnDecideTask0.getKey());
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask0.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask0.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask1.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask1.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask2.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask2.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask3.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask3.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask4.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask4.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask5.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask5.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-        autoLearnDecideState.getTaskReferences().put(autoLearnDecideTask6.getKey(),
-                new AxStateTaskReference(autoLearnDecideState.getKey(), autoLearnDecideTask6.getKey(),
-                        AxStateTaskOutputType.DIRECT, alDec2Act.getKey()));
-
-        logicReader.setDefaultLogic("DefaultState_Logic");
-
-        final AxState autoLearnEstablishState = new AxState(new AxReferenceKey(autoLearnPolicy.getKey(), "Establish"));
-        autoLearnEstablishState.setTrigger(autoLearnMatchEvent.getKey());
-        final AxStateOutput alEst2Dec = new AxStateOutput(autoLearnEstablishState.getKey(),
-                autoLearnDecideState.getKey(), autoLearnEstablishEvent.getKey());
-        autoLearnEstablishState.getStateOutputs().put(alEst2Dec.getKey().getLocalName(), alEst2Dec);
-        autoLearnEstablishState.setTaskSelectionLogic(
-                new AxTaskSelectionLogic(autoLearnEstablishState.getKey(), "TaskSelectionLogic", "MVEL", logicReader));
-        autoLearnEstablishState.setDefaultTask(autoLearnEstablishTask.getKey());
-        autoLearnEstablishState.getTaskReferences().put(autoLearnEstablishTask.getKey(),
-                new AxStateTaskReference(autoLearnEstablishState.getKey(), autoLearnEstablishTask.getKey(),
-                        AxStateTaskOutputType.DIRECT, alEst2Dec.getKey()));
-
-        final AxState autoLearnMatchState = new AxState(new AxReferenceKey(autoLearnPolicy.getKey(), "Match"));
-        autoLearnMatchState.setTrigger(autoLearnTriggerEvent.getKey());
-        final AxStateOutput alMat2Est = new AxStateOutput(autoLearnMatchState.getKey(),
-                autoLearnEstablishState.getKey(), autoLearnMatchEvent.getKey());
-        autoLearnMatchState.getStateOutputs().put(alMat2Est.getKey().getLocalName(), alMat2Est);
-        autoLearnMatchState.setTaskSelectionLogic(
-                new AxTaskSelectionLogic(autoLearnMatchState.getKey(), "TaskSelectionLogic", "MVEL", logicReader));
-        autoLearnMatchState.setDefaultTask(autoLearnMatchTask.getKey());
-        autoLearnMatchState.getTaskReferences().put(autoLearnMatchTask.getKey(),
-                new AxStateTaskReference(autoLearnMatchState.getKey(), autoLearnMatchTask.getKey(),
-                        AxStateTaskOutputType.DIRECT, alMat2Est.getKey()));
-
-        autoLearnPolicy.setFirstState(autoLearnMatchState.getKey().getLocalName());
-        autoLearnPolicy.getStateMap().put(autoLearnMatchState.getKey().getLocalName(), autoLearnMatchState);
-        autoLearnPolicy.getStateMap().put(autoLearnEstablishState.getKey().getLocalName(), autoLearnEstablishState);
-        autoLearnPolicy.getStateMap().put(autoLearnDecideState.getKey().getLocalName(), autoLearnDecideState);
-        autoLearnPolicy.getStateMap().put(autoLearnActState.getKey().getLocalName(), autoLearnActState);
-
-        final AxPolicies autoLearnPolicies = new AxPolicies(new AxArtifactKey("AutoLearnPolicies", "0.0.1"));
-        autoLearnPolicies.getPolicyMap().put(autoLearnPolicy.getKey(), autoLearnPolicy);
-
-        final AxKeyInformation keyInformation =
-                new AxKeyInformation(new AxArtifactKey("AutoLearnKeyInformation", "0.0.1"));
-        final AxPolicyModel autoLearnPolicyModel =
-                new AxPolicyModel(new AxArtifactKey("AutoLearnPolicyModel", "0.0.1"));
-        autoLearnPolicyModel.setPolicies(autoLearnPolicies);
-        autoLearnPolicyModel.setEvents(autoLearnEvents);
-        autoLearnPolicyModel.setTasks(autoLearnTasks);
-        autoLearnPolicyModel.setAlbums(autoLearnAlbums);
-        autoLearnPolicyModel.setSchemas(alContextSchemas);
-        autoLearnPolicyModel.setKeyInformation(keyInformation);
-        autoLearnPolicyModel.getKeyInformation().generateKeyInfo(autoLearnPolicyModel);
-
-        final AxValidationResult result = autoLearnPolicyModel.validate(new AxValidationResult());
-        if (!result.getValidationResult().equals(AxValidationResult.ValidationResult.VALID)) {
-            throw new ApexRuntimeException("model " + autoLearnPolicyModel.getID() + " is not valid" + result);
-        }
-        return autoLearnPolicyModel;
-    }
-
-}
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java
deleted file mode 100644
index 0cc9bd3a2..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java
+++ /dev/null
@@ -1,64 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive.model;
-
-import org.onap.policy.apex.model.basicmodel.concepts.ApexException;
-import org.onap.policy.apex.model.basicmodel.handling.ApexModelSaver;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-/**
- * This class saves sample domain models to disk in XML and JSON format.
- *
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-public final class AdaptiveDomainModelSaver {
-    /**
-     * Private default constructor to prevent subclassing.
-     */
-    private AdaptiveDomainModelSaver() {}
-
-    /**
-     * Write the AADM model to args[0].
-     *
-     * @param args Not used
-     * @throws ApexException the apex exception
-     */
-    public static void main(final String[] args) throws ApexException {
-        if (args.length != 1) {
-            System.err.println("usage: " + AdaptiveDomainModelSaver.class.getCanonicalName() + " modelDirectory");
-            return;
-        }
-
-        // Save Anomaly Detection model
-        final AxPolicyModel adPolicyModel = new AdaptiveDomainModelFactory().getAnomalyDetectionPolicyModel();
-        final ApexModelSaver<AxPolicyModel> adModelSaver =
-                new ApexModelSaver<>(AxPolicyModel.class, adPolicyModel, args[0]);
-        adModelSaver.apexModelWriteJSON();
-        adModelSaver.apexModelWriteXML();
-
-        // Save Auto Learn model
-        final AxPolicyModel alPolicyModel = new AdaptiveDomainModelFactory().getAutoLearnPolicyModel();
-        final ApexModelSaver<AxPolicyModel> alModelSaver =
-                new ApexModelSaver<>(AxPolicyModel.class, alPolicyModel, args[0]);
-        alModelSaver.apexModelWriteJSON();
-        alModelSaver.apexModelWriteXML();
-    }
-}
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java
deleted file mode 100644
index a0b2a8f40..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java
+++ /dev/null
@@ -1,414 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive.model.java;
-
-import java.util.Arrays;
-import java.util.LinkedHashMap;
-import java.util.LinkedList;
-import java.util.List;
-import java.util.Map;
-
-import org.apache.commons.math3.distribution.TDistribution;
-import org.apache.commons.math3.util.FastMath;
-import org.onap.policy.apex.core.engine.executor.context.TaskSelectionExecutionContext;
-import org.onap.policy.apex.examples.adaptive.concepts.AnomalyDetection;
-import org.onap.policy.apex.model.basicmodel.concepts.ApexException;
-import org.slf4j.Logger;
-
-/**
- * The Class AnomalyDetectionPolicy_Decide_TaskSelectionLogic.
- */
-// CHECKSTYLE:OFF: checkstyle:className
-public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
-    // CHECKSTYLE:ON: checkstyle:className
-
-    private Logger logger;
-    // configuration
-    private static final double ANOMALY_SENSITIVITY = 0.05;
-    private static final int FREQUENCY = 360;
-
-    /**
-     * A map to hold the Anomaly degree/levels/probabilities required for each task.<br>
-     * If there is no task defined for a calculated anomaly-degree, then the default task is used.<br>
-     * The map use (LinkedHashMap) is an insertion-ordered map, so the first interval matching a query is used.
-     */
-    // CHECKSTYLE:OFF: checkstyle:magicNumber
-    private static final Map<double[], String> TASK_INTERVALS = new LinkedHashMap<>();
-    static {
-        TASK_INTERVALS.put(new double[] { 0.0, 0.1 }, null); // null will mean default task
-        TASK_INTERVALS.put(new double[] { 0.25, 0.5 }, "AnomalyDetectionDecideTask1");
-        TASK_INTERVALS.put(new double[] { 0.5, 1.01 }, "AnomalyDetectionDecideTask2");
-    }
-    // CHECKSTYLE:ON: checkstyle:magicNumber
-
-    private volatile TaskSelectionExecutionContext executionContext;
-
-    /**
-     * Gets the task.
-     *
-     * @param executor the executor
-     * @return the task
-     */
-    public boolean getTask(final TaskSelectionExecutionContext executor) {
-        executionContext = executor;
-        logger = executionContext.logger;
-        logger.debug(executor.subject.getId());
-        logger.debug(executor.inFields.toString());
-        final double now = (Double) (executor.inFields.get("MonitoredValue"));
-        final Integer iteration = (Integer) (executor.inFields.get("Iteration"));
-        final double[] vals = this.forecastingAndAnomaly(now); // double[forecastedValue, AnomalyScore,
-                                                               // AnomalyProbability]
-        final double anomalyness = vals[2];
-        String task = null;
-        for (final Map.Entry<double[], String> i : TASK_INTERVALS.entrySet()) {
-            if (checkInterval(anomalyness, i.getKey())) {
-                task = i.getValue();
-                break;
-            }
-        }
-        if (task == null) {
-            executionContext.subject.getDefaultTaskKey().copyTo(executionContext.selectedTask);
-        } else {
-            executionContext.subject.getTaskKey(task).copyTo(executionContext.selectedTask);
-        }
-        if (logger.isDebugEnabled()) {
-            logger.debug(
-                    "TestAnomalyDetectionTSLPolicy0000DecideStateTaskSelectionLogic.getTask():\t************\t\t\t\t"
-                            + "Iteration:\t" + iteration + "\tValue:\t" + now + "\tForecast:\t" + vals[0]
-                            + "\tAnomalyScore:\t" + vals[1] + "\tAnomalyProbability:\t" + vals[2] + "\tInvoking Task:\t"
-                            + executionContext.selectedTask);
-        }
-        return true;
-    }
-
-    /**
-     * Anomaly detection and forecast.
-     *
-     * @param value The current value
-     * @return Null if the function can not be executed correctly, otherwise double[forecastedValue, AnomalyScore,
-     *         AnomalyProbability]
-     */
-    public double[] forecastingAndAnomaly(final double value) {
-        try {
-            executionContext.getContextAlbum("AnomalyDetectionAlbum").lockForWriting("AnomalyDetection");
-        } catch (final ApexException e) {
-            logger.error("Failed to acquire write lock on \"AnomalyDetection\" context", e);
-            return null;
-        }
-
-        // Get the context object
-        AnomalyDetection anomalyDetection =
-                (AnomalyDetection) executionContext.getContextAlbum("AnomalyDetectionAlbum").get("AnomalyDetection");
-        if (anomalyDetection == null) {
-            anomalyDetection = new AnomalyDetection();
-            executionContext.getContextAlbum("AnomalyDetectionAlbum").put("AnomalyDetection", anomalyDetection);
-        }
-
-        // Check the lists are initialized
-        if (!anomalyDetection.isInitialized()) {
-            anomalyDetection.init(FREQUENCY);
-        }
-
-        boolean unsetfirstround = false;
-
-        int frequency = anomalyDetection.getFrequency();
-        frequency = frequency + 1;
-
-        // reset frequency counter
-        if (frequency >= FREQUENCY) {
-            unsetfirstround = true;
-            frequency = 0;
-        }
-        anomalyDetection.setFrequency(frequency);
-
-        if (unsetfirstround && anomalyDetection.getFirstRound()) {
-            anomalyDetection.setFirstRound(false);
-        }
-
-        // --------- calculate the forecasted value - simple version
-        final Double lastForecast = anomalyDetection.getFrequencyForecasted().get(frequency);
-
-        // get forecast for current value
-        final double forecastedValue = lastForecast == null ? value : expMovingAverage(value, lastForecast);
-
-        // --------- calculate the anomalyScore
-        final double anomalyScore = lastForecast == null ? 0.0 : FastMath.abs(lastForecast - value);
-
-        anomalyDetection.getFrequencyForecasted().set(frequency, forecastedValue);
-
-        // anomaly score is ignored in the first frequency period
-        if (!anomalyDetection.getFirstRound()) {
-            ((LinkedList<Double>) anomalyDetection.getAnomalyScores()).addLast(anomalyScore);
-        }
-
-        // CHECKSTYLE:OFF: checkstyle:magicNumber
-        // max FREQUENCY*4 anomaly scores history
-        listSizeControl(anomalyDetection.getAnomalyScores(), FREQUENCY * 4);
-
-        // ---------- calculate the anomaly probability
-        double anomalyProbability = 0.0;
-        if (anomalyDetection.getAnomalyScores().size() > 30) {
-            // 0.5
-            anomalyProbability = gStatsTest(anomalyDetection.getAnomalyScores(), ANOMALY_SENSITIVITY);
-        }
-        // CHECKSTYLE:ON: checkstyle:magicNumber
-
-        try {
-            executionContext.getContextAlbum("AnomalyDetectionAlbum").unlockForWriting("AnomalyDetection");
-        } catch (final ApexException e) {
-            logger.error("Failed to release write lock on \"AnomalyDetection\" context", e);
-            return null;
-        }
-
-        return new double[] { forecastedValue, anomalyScore, anomalyProbability };
-    }
-
-    /**
-     * Is the passed value inside the interval, i.e. (value<interval[1] && value>=interval[0])
-     *
-     * @param value The value to check
-     * @param interval A 2 element double array describing an interval
-     * @return true if the value is between interval[0] (inclusive) and interval[1] (exclusive), i.e. (value<interval[1]
-     *         && value>=interval[0]). Otherwise false;
-     */
-    private static boolean checkInterval(final double value, final double[] interval) {
-        if (interval == null || interval.length != 2) {
-            throw new IllegalArgumentException("something other than an interval passed to checkInterval");
-        }
-        final double min = interval[0];
-        final double max = interval[1];
-        return (value < max && value >= min);
-    }
-
-    /**
-     * calculate the anomaly probability using statistical test.
-     *
-     * @param values the values
-     * @param significanceLevel the significance level
-     * @return the double
-     */
-    private static double gStatsTest(final List<Double> values, final double significanceLevel) {
-        if (isAllEqual(values)) {
-            return 0.0;
-        }
-        // the targeted value or the last value
-        final double currentV = values.get(values.size() - 1);
-        Double[] lValuesCopy = values.toArray(new Double[values.size()]);
-        Arrays.sort(lValuesCopy); // takes ~40% of method time
-        // if(logger.isDebugEnabled()){
-        // logger.debug("values:" + Arrays.toString(lValuesCopy));
-        // }
-        // get mean
-        double mean = getMean(lValuesCopy);
-        // get the test value: v
-        double v = getV(lValuesCopy, mean, true);
-        // get the p value for the test value
-        double pValue = getPValue(lValuesCopy, v, mean); // takes approx 25% of method time
-        // if(logger.isDebugEnabled()){
-        // logger.debug("pValue:" + pValue);
-        // }
-
-        // check the critical level
-        while (pValue < significanceLevel) { // takes approx 20% of method time
-            // the score value as the anomaly probability
-            final double score = (significanceLevel - pValue) / significanceLevel;
-            if (v == currentV) {
-                return score;
-            }
-            // do the critical check again for the left values
-            lValuesCopy = removevalue(lValuesCopy, v);
-            if (isAllEqual(lValuesCopy)) {
-                return 0.0;
-            }
-            // if(logger.isDebugEnabled()){
-            // logger.debug("left values:" + Arrays.toString(lValuesCopy));
-            // }
-            mean = getMean(lValuesCopy);
-            v = getV(lValuesCopy, mean, true);
-            pValue = getPValue(lValuesCopy, v, mean);
-        }
-        return 0.0;
-    }
-
-    /**
-     * get the test value based on mean from sorted values.
-     *
-     * @param lValues the l values
-     * @param mean the mean
-     * @param maxValueOnly : only the max extreme value will be tested
-     * @return the value to be tested
-     */
-    private static double getV(final Double[] lValues, final double mean, final boolean maxValueOnly) {
-        double v = lValues[lValues.length - 1];
-        // max value as the extreme value
-        if (maxValueOnly) {
-            return v;
-        }
-        // check the extreme side
-        if ((v - mean) < (mean - lValues[0])) {
-            v = lValues[0];
-        }
-        return v;
-    }
-
-    /**
-     * calculate the P value for the t distribution.
-     *
-     * @param lValues the l values
-     * @param v the v
-     * @param mean the mean
-     * @return the p value
-     */
-    private static double getPValue(final Double[] lValues, final double v, final double mean) {
-        // calculate z value
-        final double z = FastMath.abs(v - mean) / getStdDev(lValues, mean);
-        // logger.debug("z: " + z);
-        // calculate T
-        final double n = lValues.length;
-        final double s = (z * z * n * (2.0 - n)) / (z * z * n - (n - 1.0) * (n - 1.0));
-        final double t = FastMath.sqrt(s);
-        // logger.debug("t:" + t);
-        // default p value = 0
-        double pValue = 0.0;
-        if (!Double.isNaN(t)) {
-            // t distribution with n-2 degrees of freedom
-            final TDistribution tDist = new TDistribution(n - 2);
-            pValue = n * (1.0 - tDist.cumulativeProbability(t));
-            // set max pValue = 1
-            pValue = pValue > 1.0 ? 1.0 : pValue;
-        }
-        // logger.debug("value: "+ v + " , pValue: " + pValue);
-        return pValue;
-    }
-
-    /*
-     * Some utility methods
-     */
-    // exponential = 2(n+1)
-    private static final double EMA_EXPONENT = 2.0 / (7.0 + 1.0);
-    private static final double EMA_EXPONENT_1 = (1.0 - EMA_EXPONENT);
-
-    /**
-     * exponential moving average.
-     *
-     * @param value the value
-     * @param lastForecast the last forecast
-     * @return the double
-     */
-    private static double expMovingAverage(final double value, final double lastForecast) {
-        return (value * EMA_EXPONENT) + (lastForecast * EMA_EXPONENT_1);
-    }
-
-    /**
-     * Remove the first occurence of the value v from the array.
-     *
-     * @param lValues the l values
-     * @param v the v
-     * @return the double[]
-     */
-    private static Double[] removevalue(final Double[] lValues, final double v) {
-        for (int i = 0; i < lValues.length; i++) {
-            if (lValues[i] == v) {
-                final Double[] ret = new Double[lValues.length - 1];
-                System.arraycopy(lValues, 0, ret, 0, i);
-                System.arraycopy(lValues, i + 1, ret, i, lValues.length - i - 1);
-                return ret;
-            }
-        }
-        return lValues;
-    }
-
-    /**
-     * get mean value of double list.
-     *
-     * @param lValues the l values
-     * @return the mean
-     */
-    private static double getMean(final Double[] lValues) {
-        double sum = 0.0;
-        for (final double d : lValues) {
-
-            sum += d;
-        }
-        return sum / lValues.length;
-    }
-
-    /**
-     * get standard deviation of double list.
-     *
-     * @param lValues the l values
-     * @param mean the mean
-     * @return stddev
-     */
-    private static double getStdDev(final Double[] lValues, final double mean) {
-        double temp = 0.0;
-        for (final double d : lValues) {
-            temp += (mean - d) * (mean - d);
-        }
-        return FastMath.sqrt(temp / lValues.length);
-    }
-
-    /**
-     * Chop head off list to make it length max .
-     *
-     * @param list the list to chop
-     * @param max the max size
-     */
-    private static void listSizeControl(final List<?> list, final int max) {
-        final int k = list.size();
-        if (k > max) {
-            // Chop the head off the list.
-            list.subList(0, k - max).clear();
-        }
-    }
-
-    /**
-     * return true if all values are equal.
-     *
-     * @param lValues the l values
-     * @return true, if checks if is all equal
-     */
-    private static boolean isAllEqual(final List<Double> lValues) {
-        final double first = lValues.get(0);
-        for (final Double d : lValues) {
-            if (d != first) {
-                return false;
-            }
-        }
-        return true;
-    }
-
-    /**
-     * return true if all values are equal.
-     *
-     * @param lValues the l values
-     * @return true, if checks if is all equal
-     */
-    private static boolean isAllEqual(final Double[] lValues) {
-        final double first = lValues[0];
-        for (final Double d : lValues) {
-            if (d != first) {
-                return false;
-            }
-        }
-        return true;
-    }
-}
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AutoLearnPolicy_Decide_TaskSelectionLogic.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AutoLearnPolicy_Decide_TaskSelectionLogic.java
deleted file mode 100644
index 23d4e2486..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AutoLearnPolicy_Decide_TaskSelectionLogic.java
+++ /dev/null
@@ -1,151 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive.model.java;
-
-import java.util.Arrays;
-import java.util.List;
-import java.util.Random;
-
-import org.onap.policy.apex.context.ContextException;
-import org.onap.policy.apex.core.engine.executor.context.TaskSelectionExecutionContext;
-import org.onap.policy.apex.examples.adaptive.concepts.AutoLearn;
-
-/**
- * The Class AutoLearnPolicy_Decide_TaskSelectionLogic.
- */
-// CHECKSTYLE:OFF: checkstyle:typeName
-public class AutoLearnPolicy_Decide_TaskSelectionLogic {
-    // CHECKSTYLE:ON: checkstyle:typeName
-    private static final Random RAND = new Random(System.currentTimeMillis());
-    private static final double WANT = 50.0;
-    private int size;
-
-    /**
-     * Gets the task.
-     *
-     * @param executor the executor
-     * @return the task
-     */
-    public boolean getTask(final TaskSelectionExecutionContext executor) {
-        executor.logger.debug(executor.subject.getId());
-        executor.logger.debug(executor.inFields.toString());
-        final List<String> tasks = executor.subject.getTaskNames();
-        size = tasks.size();
-
-        try {
-            executor.getContextAlbum("AutoLearnAlbum").lockForWriting("AutoLearn");
-        } catch (final ContextException e) {
-            executor.logger.error("Failed to acquire write lock on \"autoLearn\" context", e);
-            return false;
-        }
-
-        // Get the context object
-        AutoLearn autoLearn = (AutoLearn) executor.getContextAlbum("AutoLearnAlbum").get("AutoLearn");
-        if (autoLearn == null) {
-            autoLearn = new AutoLearn();
-        }
-
-        // Check the lists are initialized
-        if (!autoLearn.isInitialized()) {
-            autoLearn.init(size);
-        }
-
-        final double now = (Double) (executor.inFields.get("MonitoredValue"));
-        final double diff = now - WANT;
-        final int option = getOption(diff, autoLearn);
-        learn(option, diff, autoLearn);
-
-        executor.getContextAlbum("AutoLearnAlbum").put("AutoLearnAlbum", autoLearn);
-
-        try {
-            executor.getContextAlbum("AutoLearnAlbum").unlockForWriting("AutoLearn");
-        } catch (final ContextException e) {
-            executor.logger.error("Failed to acquire write lock on \"autoLearn\" context", e);
-            return false;
-        }
-
-        executor.subject.getTaskKey(tasks.get(option)).copyTo(executor.selectedTask);
-        return true;
-    }
-
-    /**
-     * Gets the option.
-     *
-     * @param diff the diff
-     * @param autoLearn the auto learn
-     * @return the option
-     */
-    private int getOption(final double diff, final AutoLearn autoLearn) {
-        final Double[] avdiffs = autoLearn.getAvDiffs().toArray(new Double[autoLearn.getAvDiffs().size()]);
-        final int r = RAND.nextInt(size);
-        int closestupi = -1;
-        int closestdowni = -1;
-        double closestup = Double.MAX_VALUE;
-        double closestdown = Double.MIN_VALUE;
-        for (int i = 0; i < size; i++) {
-            if (Double.isNaN(avdiffs[i])) {
-                return r;
-            }
-            if (avdiffs[i] >= diff && avdiffs[i] <= closestup) {
-                closestup = avdiffs[i];
-                closestupi = i;
-            }
-            if (avdiffs[i] <= diff && avdiffs[i] >= closestdown) {
-                closestdown = avdiffs[i];
-                closestdowni = i;
-            }
-        }
-        if (closestupi == -1 || closestdowni == -1) {
-            return r;
-        }
-        if (closestupi == closestdowni) {
-            return closestupi;
-        }
-        if (Math.abs(closestdown - diff) > Math.abs(closestup - diff)) {
-            return closestupi;
-        } else {
-            return closestdowni;
-        }
-    }
-
-    /**
-     * Learn.
-     *
-     * @param option the option
-     * @param diff the diff
-     * @param autoLearn the auto learn
-     */
-    private void learn(final int option, final double diff, final AutoLearn autoLearn) {
-        final Double[] avdiffs = autoLearn.getAvDiffs().toArray(new Double[autoLearn.getAvDiffs().size()]);
-        final Long[] counts = autoLearn.getCounts().toArray(new Long[autoLearn.getCounts().size()]);
-        if (option < 0 || option >= avdiffs.length) {
-            throw new IllegalArgumentException("Error: option" + option);
-        }
-        counts[option]++;
-        if (Double.isNaN(avdiffs[option])) {
-            avdiffs[option] = diff;
-        } else {
-            avdiffs[option] = (avdiffs[option] * (counts[option] - 1) + diff) / counts[option];
-        }
-        autoLearn.setAvDiffs(Arrays.asList(avdiffs));
-        autoLearn.setCounts(Arrays.asList(counts));
-    }
-}
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/package-info.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/package-info.java
deleted file mode 100644
index 172be5ada..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/package-info.java
+++ /dev/null
@@ -1,27 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-/**
- * Pprovides task selection logic for the adaptive domain in Java.
- *
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-
-package org.onap.policy.apex.examples.adaptive.model.java;
diff --git a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/package-info.java b/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/package-info.java
deleted file mode 100644
index d38333ba8..000000000
--- a/examples/adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/package-info.java
+++ /dev/null
@@ -1,27 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-/**
- * Provides Java generation of the Adaptive model as well as Java task selection logic for the domain.
- *
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-
-package org.onap.policy.apex.examples.adaptive.model;
diff --git a/examples/adaptive/src/main/resources/examples/events/Adaptive/AnomalyDetectionEvents.json b/examples/adaptive/src/main/resources/examples/events/Adaptive/AnomalyDetectionEvents.json
deleted file mode 100644
index 2872f5ae4..000000000
--- a/examples/adaptive/src/main/resources/examples/events/Adaptive/AnomalyDetectionEvents.json
+++ /dev/null
@@ -1,200 +0,0 @@
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 0,
-    "MonitoredValue": 0.04818448765182781
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.016856740089812434,
-    "Iteration": 1
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 2,
-    "MonitoredValue": 0.07283031742656552
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 3,
-    "MonitoredValue": 0.05284674407712258
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.08685406312054446,
-    "Iteration": 4
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.09580382706345814,
-    "Iteration": 5
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 6,
-    "MonitoredValue": 0.07022220893167114
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.05027456879617627,
-    "Iteration": 7
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 8,
-    "MonitoredValue": 0.16867139038930964
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.18383434112759453,
-    "Iteration": 9
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 10,
-    "MonitoredValue": 0.11940188164467769
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 11,
-    "MonitoredValue": 0.18528189685974508
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.19934812597926355,
-    "Iteration": 12
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.2769320946213342,
-    "Iteration": 13
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 14,
-    "MonitoredValue": 0.2573073533232842
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 15,
-    "MonitoredValue": 0.2114736039819203
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.3070179558734792,
-    "Iteration": 16
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.22817748171407137,
-    "Iteration": 17
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "Iteration": 18,
-    "MonitoredValue": 0.3742338965886025
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AnomalyDetectionTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 0.33767889848226273,
-    "Iteration": 19
-}
-
diff --git a/examples/adaptive/src/main/resources/examples/events/Adaptive/AutoLearnEvents.json b/examples/adaptive/src/main/resources/examples/events/Adaptive/AutoLearnEvents.json
deleted file mode 100644
index 4a90c944d..000000000
--- a/examples/adaptive/src/main/resources/examples/events/Adaptive/AutoLearnEvents.json
+++ /dev/null
@@ -1,10000 +0,0 @@
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 0.0,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 77.69433155254976,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 78.80403683294003
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 78.8005362087235,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 77.70005535199167
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 78.79813005686083
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 77.6625792808998
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
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-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 77.43985768687475
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 77.22866213897053
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 77.89674604484705,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 75.24961836787988
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 74.25243852072533
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 77.01106311345667
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 90.42073086787556,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 79.64186930310875
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 63.47357695595852
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "LastMonitoredValue": 71.55772312953363,
-    "MonitoredValue": 76.94715391191704
-}
-
-{
-    "nameSpace": "org.onap.policy.apex.examples.adaptive.events",
-    "name": "AutoLearnTriggerEvent",
-    "version": "0.0.1",
-    "source": "CompaA",
-    "target": "apex",
-    "MonitoredValue": 76.94715391191704,
-    "LastMonitoredValue": 82.33658469430046
-}
-
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask0_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask0_TaskLogic.mvel
deleted file mode 100644
index 758062b8e..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask0_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask0: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = (1.0/2.0) * (Math.abs(inval - WANT));
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret<MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask0: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask1_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask1_TaskLogic.mvel
deleted file mode 100644
index 051766045..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask1_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask1: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = (1.0/5.0) * (Math.abs(inval - WANT));
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret<MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask1: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask2_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask2_TaskLogic.mvel
deleted file mode 100644
index b787b2153..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask2_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask2: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = (1.0/10.0) * (Math.abs(inval - WANT));
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret<MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask2: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask3_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask3_TaskLogic.mvel
deleted file mode 100644
index 7fbc8c765..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask3_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask3: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = rand.nextGaussian()*((MAX - WANT) / 50.0);
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret<MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask3: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask4_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask4_TaskLogic.mvel
deleted file mode 100644
index a0a12d84f..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask4_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask4: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = (-1.0/10.0) * (Math.abs(inval - WANT));
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret<MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask4: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask5_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask5_TaskLogic.mvel
deleted file mode 100644
index fc2005fdf..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask5_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask5: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = (-1.0/5.0) * (Math.abs(inval - WANT));
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret < MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask5: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask6_TaskLogic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask6_TaskLogic.mvel
deleted file mode 100644
index 5eb44839c..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/AutoLearnDecideTask6_TaskLogic.mvel
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnDecideTask6: inFields:" + inFields);
-java.util.Random rand = new java.util.Random(System.currentTimeMillis());
-double MIN = -100.0;
-double MAX = 100.0;
-double WANT = 50.0;
-
-double inval = (Double)(inFields["MonitoredValue"]);
-double ret = inval;
-///////////////
-double diff = (-1.0/2.0) * (Math.abs(inval - WANT));
-///////////////
-ret = inval + diff;
-if (ret > MAX)
-    ret = MAX;
-if (ret<MIN)
-    ret = MIN;
-
-outFields["MonitoredValue"] = ret;
-outFields["LastMonitoredValue"] = inval;
-logger.debug("AutoLearnDecideTask6: outFields:" + outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultAnomalyDetectionTask_Logic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultAnomalyDetectionTask_Logic.mvel
deleted file mode 100644
index 8f894d297..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultAnomalyDetectionTask_Logic.mvel
+++ /dev/null
@@ -1,25 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug(subject.getTaskName() + " execution logic");
-logger.debug("inFields : " + inFields);
-outFields["MonitoredValue"] = inFields["MonitoredValue"];
-outFields["Iteration"] = inFields["Iteration"];
-logger.debug("outFields : "+outFields);
-return true;
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultAutoLearnTask_Logic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultAutoLearnTask_Logic.mvel
deleted file mode 100644
index 636378396..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultAutoLearnTask_Logic.mvel
+++ /dev/null
@@ -1,26 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug("AutoLearnActTask execution logic");
-logger.debug("inFields : " + inFields);
-outFields["MonitoredValue"] = inFields["MonitoredValue"];
-outFields["LastMonitoredValue"] = inFields["LastMonitoredValue"];
-logger.debug("outFields : " + outFields);
-return true;
-
diff --git a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultState_Logic.mvel b/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultState_Logic.mvel
deleted file mode 100644
index 2db0a0031..000000000
--- a/examples/adaptive/src/main/resources/org/onap/policy/apex/examples/adaptive/model/mvel/DefaultState_Logic.mvel
+++ /dev/null
@@ -1,23 +0,0 @@
-/*
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- * 
- *      http://www.apache.org/licenses/LICENSE-2.0
- * 
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * 
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-logger.debug(subject.id + ":" + subject.stateName);
-subject.defaultTaskKey.copyTo(selectedTask);
-logger.debug(subject.id + ":" + subject.stateName) + ", using default task" + subject.defaultTaskKey.getID();
-return true;
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDBWrite.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDBWrite.java
deleted file mode 100644
index 898531c32..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDBWrite.java
+++ /dev/null
@@ -1,60 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import java.io.File;
-import java.sql.Connection;
-import java.sql.DriverManager;
-
-import org.junit.After;
-import org.junit.Before;
-import org.junit.Test;
-import org.onap.policy.apex.model.basicmodel.dao.DAOParameters;
-import org.onap.policy.apex.model.basicmodel.test.TestApexModel;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-public class TestAnomalyDetectionDBWrite {
-    private Connection connection;
-    TestApexModel<AxPolicyModel> testApexModel;
-
-    @Before
-    public void setup() throws Exception {
-        Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
-        connection = DriverManager.getConnection("jdbc:derby:memory:apex_test;create=true");
-
-        testApexModel = new TestApexModel<>(AxPolicyModel.class, new TestAnomalyDetectionModelCreator());
-    }
-
-    @After
-    public void teardown() throws Exception {
-        connection.close();
-        new File("derby.log").delete();
-    }
-
-    @Test
-    public void testModelWriteReadJPA() throws Exception {
-        final DAOParameters daoParameters = new DAOParameters();
-        daoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
-        daoParameters.setPersistenceUnit("AdaptiveModelsTest");
-
-        testApexModel.testApexModelWriteReadJPA(daoParameters);
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java
deleted file mode 100644
index 7e2fb0eb7..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java
+++ /dev/null
@@ -1,81 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import static org.junit.Assert.assertTrue;
-
-import java.io.File;
-import java.sql.Connection;
-import java.sql.DriverManager;
-
-import org.junit.After;
-import org.junit.Before;
-import org.junit.Test;
-import org.onap.policy.apex.model.basicmodel.concepts.AxValidationResult;
-import org.onap.policy.apex.model.basicmodel.dao.DAOParameters;
-import org.onap.policy.apex.model.basicmodel.test.TestApexModel;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-public class TestAnomalyDetectionModel {
-    private Connection connection;
-    TestApexModel<AxPolicyModel> testApexModel;
-
-    @Before
-    public void setup() throws Exception {
-        Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
-        connection = DriverManager.getConnection("jdbc:derby:memory:apex_test;create=true");
-
-        testApexModel = new TestApexModel<>(AxPolicyModel.class, new TestAnomalyDetectionModelCreator());
-    }
-
-    @After
-    public void teardown() throws Exception {
-        connection.close();
-        new File("derby.log").delete();
-    }
-
-    @Test
-    public void testModelValid() throws Exception {
-        final AxValidationResult result = testApexModel.testApexModelValid();
-        assertTrue(result.toString().equals(VALID_MODEL_STRING));
-    }
-
-    @Test
-    public void testModelWriteReadXML() throws Exception {
-        testApexModel.testApexModelWriteReadXML();
-    }
-
-    @Test
-    public void testModelWriteReadJSON() throws Exception {
-        testApexModel.testApexModelWriteReadJSON();
-    }
-
-    @Test
-    public void testModelWriteReadJPA() throws Exception {
-        final DAOParameters daoParameters = new DAOParameters();
-        daoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
-        daoParameters.setPersistenceUnit("AdaptiveModelsTest");
-
-        testApexModel.testApexModelWriteReadJPA(daoParameters);
-    }
-
-    private static final String VALID_MODEL_STRING = "***validation of model successful***";
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java
deleted file mode 100644
index 2b50d69ab..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java
+++ /dev/null
@@ -1,56 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import org.onap.policy.apex.examples.adaptive.model.AdaptiveDomainModelFactory;
-import org.onap.policy.apex.model.basicmodel.test.TestApexModelCreator;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-/**
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-public class TestAnomalyDetectionModelCreator implements TestApexModelCreator<AxPolicyModel> {
-
-    @Override
-    public AxPolicyModel getModel() {
-        return new AdaptiveDomainModelFactory().getAnomalyDetectionPolicyModel();
-    }
-
-    @Override
-    public AxPolicyModel getMalstructuredModel() {
-        return null;
-    }
-
-    @Override
-    public AxPolicyModel getObservationModel() {
-        return null;
-    }
-
-    @Override
-    public AxPolicyModel getWarningModel() {
-        return getModel();
-    }
-
-    @Override
-    public AxPolicyModel getInvalidModel() {
-        return null;
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTSLUseCase.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTSLUseCase.java
deleted file mode 100644
index 7d9791d46..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTSLUseCase.java
+++ /dev/null
@@ -1,164 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import static org.junit.Assert.assertEquals;
-import static org.junit.Assert.assertNotNull;
-import static org.junit.Assert.assertTrue;
-
-import java.io.IOException;
-import java.util.Random;
-
-import org.junit.Test;
-import org.onap.policy.apex.core.engine.EngineParameters;
-import org.onap.policy.apex.core.engine.engine.ApexEngine;
-import org.onap.policy.apex.core.engine.engine.impl.ApexEngineFactory;
-import org.onap.policy.apex.core.engine.event.EnEvent;
-import org.onap.policy.apex.examples.adaptive.model.AdaptiveDomainModelFactory;
-import org.onap.policy.apex.model.basicmodel.concepts.ApexException;
-import org.onap.policy.apex.model.basicmodel.concepts.AxArtifactKey;
-import org.onap.policy.apex.model.basicmodel.concepts.AxValidationResult;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-import org.onap.policy.apex.plugins.executor.java.JavaExecutorParameters;
-import org.onap.policy.apex.plugins.executor.mvel.MVELExecutorParameters;
-import org.slf4j.ext.XLogger;
-import org.slf4j.ext.XLoggerFactory;
-
-/**
- * This policy passes, and recieves a Double event context filed called "EVCDouble".<br>
- * The policy tries to detect anomalies in the pattern of values for EVCDouble<br>
- * See the 2 test cases below (1 short, 1 long)
- *
- * @author John Keeney (John.Keeney@ericsson.com)
- */
-public class TestAnomalyDetectionTSLUseCase {
-    private static final XLogger LOGGER = XLoggerFactory.getXLogger(TestAnomalyDetectionTSLUseCase.class);
-
-    private static final int MAXITERATIONS = 3660;
-    private static final Random RAND = new Random(System.currentTimeMillis());
-
-    @Test
-    // once through the long running test below
-    public void TestAnomalyDetectionTSL() throws ApexException, InterruptedException, IOException {
-        final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAnomalyDetectionPolicyModel();
-        assertNotNull(apexPolicyModel);
-
-        final AxValidationResult validationResult = new AxValidationResult();
-        apexPolicyModel.validate(validationResult);
-        assertTrue(validationResult.isValid());
-
-        final AxArtifactKey key = new AxArtifactKey("AnomalyTSLApexEngine", "0.0.1");
-        final EngineParameters parameters = new EngineParameters();
-        parameters.getExecutorParameterMap().put("MVEL", new MVELExecutorParameters());
-        parameters.getExecutorParameterMap().put("JAVA", new JavaExecutorParameters());
-
-        final ApexEngine apexEngine1 = new ApexEngineFactory().createApexEngine(key);
-
-        final TestApexActionListener listener1 = new TestApexActionListener("TestListener1");
-        apexEngine1.addEventListener("listener", listener1);
-        apexEngine1.updateModel(apexPolicyModel);
-        apexEngine1.start();
-        final EnEvent triggerEvent =
-                apexEngine1.createEvent(new AxArtifactKey("AnomalyDetectionTriggerEvent", "0.0.1"));
-        final double rval = RAND.nextGaussian();
-        triggerEvent.put("Iteration", 0);
-        triggerEvent.put("MonitoredValue", rval);
-        LOGGER.info("Triggering policy in Engine 1 with " + triggerEvent);
-        apexEngine1.handleEvent(triggerEvent);
-        final EnEvent result = listener1.getResult();
-        LOGGER.info("Receiving action event {} ", result);
-        assertEquals("ExecutionIDs are different", triggerEvent.getExecutionID(), result.getExecutionID());
-        triggerEvent.clear();
-        result.clear();
-        Thread.sleep(1);
-        apexEngine1.stop();
-    }
-
-    /**
-     * This policy passes, and recieves a Double event context filed called "EVCDouble"<br>
-     * The policy tries to detect anomalies in the pattern of values for EVCDouble <br>
-     * This test case generates a SineWave-like pattern for the parameter, repeating every 360 iterations. (These Period
-     * should probably be set using TaskParameters!) Every 361st value is a random number!, so should be identified as
-     * an Anomaly. The policy has 3 Decide Tasks, and the Decide TaskSelectionLogic picks one depending on the
-     * 'Anomaliness' of the input data. <br>
-     * To plot the results grep debug results for the string "************", paste into excel and delete non-relevant
-     * columns<br>
-     *
-     * @throws ApexException the apex exception
-     * @throws InterruptedException the interrupted exception
-     * @throws IOException Signals that an I/O exception has occurred.
-     */
-    // Test is disabled by default. uncomment below, or execute using the main() method
-    // @Test
-    // EG Dos command: apex-core.engine> mvn
-    // -Dtest=org.onap.policy.apex.core.engine.ml.TestAnomalyDetectionTSLUseCase test | findstr /L /C:"Apex [main] DEBUG
-    // c.e.a.e.TaskSelectionExecutionLogging -
-    // TestAnomalyDetectionTSL_Policy0000DecideStateTaskSelectionLogic.getTask():"
-    public void TestAnomalyDetectionTSL_main() throws ApexException, InterruptedException, IOException {
-
-        final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAnomalyDetectionPolicyModel();
-        assertNotNull(apexPolicyModel);
-
-        final AxValidationResult validationResult = new AxValidationResult();
-        apexPolicyModel.validate(validationResult);
-        assertTrue(validationResult.isValid());
-
-        final AxArtifactKey key = new AxArtifactKey("AnomalyTSLApexEngine", "0.0.1");
-        final EngineParameters parameters = new EngineParameters();
-        parameters.getExecutorParameterMap().put("MVEL", new MVELExecutorParameters());
-        parameters.getExecutorParameterMap().put("JAVA", new JavaExecutorParameters());
-
-        final ApexEngine apexEngine1 = new ApexEngineFactory().createApexEngine(key);
-
-        final TestApexActionListener listener1 = new TestApexActionListener("TestListener1");
-        apexEngine1.addEventListener("listener1", listener1);
-        apexEngine1.updateModel(apexPolicyModel);
-        apexEngine1.start();
-
-        final EnEvent triggerEvent =
-                apexEngine1.createEvent(new AxArtifactKey("AnomalyDetectionTriggerEvent", "0.0.1"));
-        assertNotNull(triggerEvent);
-
-        for (int iteration = 0; iteration < MAXITERATIONS; iteration++) {
-            // Trigger the policy in engine 1
-
-            double value = (Math.sin(Math.toRadians(iteration))) + (RAND.nextGaussian() / 25.0);
-            // lets make every 361st number a random value to perhaps flag as an anomaly
-            if (((iteration + 45) % 361) == 0) {
-                value = (RAND.nextGaussian() * 2.0);
-            }
-            triggerEvent.put("Iteration", iteration);
-            triggerEvent.put("MonitoredValue", value);
-            LOGGER.info("Iteration " + iteration + ":\tTriggering policy in Engine 1 with " + triggerEvent);
-            apexEngine1.handleEvent(triggerEvent);
-            final EnEvent result = listener1.getResult();
-            LOGGER.info("Iteration " + iteration + ":\tReceiving action event {} ", result);
-            triggerEvent.clear();
-            result.clear();
-        }
-        apexEngine1.stop();
-        Thread.sleep(1000);
-    }
-
-    public static void main(final String[] args) throws ApexException, InterruptedException, IOException {
-        new TestAnomalyDetectionTSLUseCase().TestAnomalyDetectionTSL_main();
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestApexActionListener.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestApexActionListener.java
deleted file mode 100644
index ec7c197b7..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestApexActionListener.java
+++ /dev/null
@@ -1,91 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import java.util.ArrayList;
-import java.util.List;
-
-import org.onap.policy.apex.core.engine.engine.EnEventListener;
-import org.onap.policy.apex.core.engine.event.EnEvent;
-import org.onap.policy.apex.core.infrastructure.threading.ThreadUtilities;
-
-/**
- * The listener interface for receiving testApexAction events. The class that is interested in processing a
- * testApexAction event implements this interface, and the object created with that class is registered with a component
- * using the component's <code>addTestApexActionListener</code> method. When the testApexAction event occurs, that
- * object's appropriate method is invoked.
- *
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-public class TestApexActionListener implements EnEventListener {
-    private List<EnEvent> resultEvents = new ArrayList<>();
-
-    private final String id;
-
-    /**
-     * Instantiates a new test apex action listener.
-     *
-     * @param id the id
-     */
-    public TestApexActionListener(final String id) {
-        this.id = id;
-    }
-
-    /**
-     * Gets the result.
-     *
-     * @return the result
-     */
-    public EnEvent getResult() {
-        while (resultEvents.isEmpty()) {
-            ThreadUtilities.sleep(100);
-        }
-        return resultEvents.remove(0);
-    }
-
-    /*
-     * (non-Javadoc)
-     *
-     * @see
-     * org.onap.policy.apex.core.engine.engine.EnEventListener#onEnEvent(org.onap.policy.apex.core.engine.event.EnEvent)
-     */
-    @Override
-    public void onEnEvent(final EnEvent actionEvent) {
-        try {
-            Thread.sleep(100);
-        } catch (final InterruptedException e) {
-            e.printStackTrace();
-        }
-        if (actionEvent != null) {
-            System.out.println("Action event from engine:" + actionEvent.getName());
-            resultEvents.add(actionEvent);
-        }
-    }
-
-    /**
-     * Gets the id.
-     *
-     * @return the id
-     */
-    public String getId() {
-        return id;
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDBWrite.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDBWrite.java
deleted file mode 100644
index 64efa6c35..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDBWrite.java
+++ /dev/null
@@ -1,60 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import java.io.File;
-import java.sql.Connection;
-import java.sql.DriverManager;
-
-import org.junit.After;
-import org.junit.Before;
-import org.junit.Test;
-import org.onap.policy.apex.model.basicmodel.dao.DAOParameters;
-import org.onap.policy.apex.model.basicmodel.test.TestApexModel;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-public class TestAutoLearnDBWrite {
-    private Connection connection;
-    TestApexModel<AxPolicyModel> testApexModel;
-
-    @Before
-    public void setup() throws Exception {
-        Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
-        connection = DriverManager.getConnection("jdbc:derby:memory:apex_test;create=true");
-
-        testApexModel = new TestApexModel<>(AxPolicyModel.class, new TestAutoLearnModelCreator());
-    }
-
-    @After
-    public void teardown() throws Exception {
-        connection.close();
-        new File("derby.log").delete();
-    }
-
-    @Test
-    public void testModelWriteReadJPA() throws Exception {
-        final DAOParameters daoParameters = new DAOParameters();
-        daoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
-        daoParameters.setPersistenceUnit("AdaptiveModelsTest");
-
-        testApexModel.testApexModelWriteReadJPA(daoParameters);
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java
deleted file mode 100644
index aa7f621c9..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java
+++ /dev/null
@@ -1,81 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import static org.junit.Assert.assertTrue;
-
-import java.io.File;
-import java.sql.Connection;
-import java.sql.DriverManager;
-
-import org.junit.After;
-import org.junit.Before;
-import org.junit.Test;
-import org.onap.policy.apex.model.basicmodel.concepts.AxValidationResult;
-import org.onap.policy.apex.model.basicmodel.dao.DAOParameters;
-import org.onap.policy.apex.model.basicmodel.test.TestApexModel;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-public class TestAutoLearnModel {
-    private Connection connection;
-    TestApexModel<AxPolicyModel> testApexModel;
-
-    @Before
-    public void setup() throws Exception {
-        Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
-        connection = DriverManager.getConnection("jdbc:derby:memory:apex_test;create=true");
-
-        testApexModel = new TestApexModel<>(AxPolicyModel.class, new TestAutoLearnModelCreator());
-    }
-
-    @After
-    public void teardown() throws Exception {
-        connection.close();
-        new File("derby.log").delete();
-    }
-
-    @Test
-    public void testModelValid() throws Exception {
-        final AxValidationResult result = testApexModel.testApexModelValid();
-        assertTrue(result.toString().equals(VALID_MODEL_STRING));
-    }
-
-    @Test
-    public void testModelWriteReadXML() throws Exception {
-        testApexModel.testApexModelWriteReadXML();
-    }
-
-    @Test
-    public void testModelWriteReadJSON() throws Exception {
-        testApexModel.testApexModelWriteReadJSON();
-    }
-
-    @Test
-    public void testModelWriteReadJPA() throws Exception {
-        final DAOParameters daoParameters = new DAOParameters();
-        daoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
-        daoParameters.setPersistenceUnit("AdaptiveModelsTest");
-
-        testApexModel.testApexModelWriteReadJPA(daoParameters);
-    }
-
-    private static final String VALID_MODEL_STRING = "***validation of model successful***";
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java
deleted file mode 100644
index 11f1991bf..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java
+++ /dev/null
@@ -1,56 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import org.onap.policy.apex.examples.adaptive.model.AdaptiveDomainModelFactory;
-import org.onap.policy.apex.model.basicmodel.test.TestApexModelCreator;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-
-/**
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-public class TestAutoLearnModelCreator implements TestApexModelCreator<AxPolicyModel> {
-
-    @Override
-    public AxPolicyModel getModel() {
-        return new AdaptiveDomainModelFactory().getAutoLearnPolicyModel();
-    }
-
-    @Override
-    public AxPolicyModel getMalstructuredModel() {
-        return null;
-    }
-
-    @Override
-    public AxPolicyModel getObservationModel() {
-        return null;
-    }
-
-    @Override
-    public AxPolicyModel getWarningModel() {
-        return getModel();
-    }
-
-    @Override
-    public AxPolicyModel getInvalidModel() {
-        return null;
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTSLUseCase.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTSLUseCase.java
deleted file mode 100644
index 88b504cef..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTSLUseCase.java
+++ /dev/null
@@ -1,187 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-package org.onap.policy.apex.examples.adaptive;
-
-import static org.junit.Assert.assertEquals;
-import static org.junit.Assert.assertNotNull;
-import static org.junit.Assert.assertTrue;
-
-import java.io.IOException;
-import java.util.Random;
-
-import org.junit.Test;
-import org.onap.policy.apex.core.engine.EngineParameters;
-import org.onap.policy.apex.core.engine.engine.ApexEngine;
-import org.onap.policy.apex.core.engine.engine.impl.ApexEngineFactory;
-import org.onap.policy.apex.core.engine.event.EnEvent;
-import org.onap.policy.apex.examples.adaptive.model.AdaptiveDomainModelFactory;
-import org.onap.policy.apex.model.basicmodel.concepts.ApexException;
-import org.onap.policy.apex.model.basicmodel.concepts.AxArtifactKey;
-import org.onap.policy.apex.model.basicmodel.concepts.AxValidationResult;
-import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-import org.onap.policy.apex.plugins.executor.java.JavaExecutorParameters;
-import org.onap.policy.apex.plugins.executor.mvel.MVELExecutorParameters;
-import org.slf4j.ext.XLogger;
-import org.slf4j.ext.XLoggerFactory;
-
-/**
- * Test Auto learning in TSL.
- *
- * @author John Keeney (John.Keeney@ericsson.com)
- */
-public class TestAutoLearnTSLUseCase {
-    private static final XLogger LOGGER = XLoggerFactory.getXLogger(TestAutoLearnTSLUseCase.class);
-
-    private static final int MAXITERATIONS = 1000;
-    private static final Random rand = new Random(System.currentTimeMillis());
-
-    @Test
-    // once through the long running test below
-    public void TestAutoLearnTSL() throws ApexException, InterruptedException, IOException {
-        final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAutoLearnPolicyModel();
-        assertNotNull(apexPolicyModel);
-
-        final AxValidationResult validationResult = new AxValidationResult();
-        apexPolicyModel.validate(validationResult);
-        assertTrue(validationResult.isValid());
-
-        final AxArtifactKey key = new AxArtifactKey("AADMApexEngine", "0.0.1");
-        final EngineParameters parameters = new EngineParameters();
-        parameters.getExecutorParameterMap().put("MVEL", new MVELExecutorParameters());
-        parameters.getExecutorParameterMap().put("JAVA", new JavaExecutorParameters());
-
-        final ApexEngine apexEngine1 = new ApexEngineFactory().createApexEngine(key);
-
-        final TestApexActionListener listener1 = new TestApexActionListener("TestListener1");
-        apexEngine1.addEventListener("listener", listener1);
-        apexEngine1.updateModel(apexPolicyModel);
-        apexEngine1.start();
-        final EnEvent triggerEvent = apexEngine1.createEvent(new AxArtifactKey("AutoLearnTriggerEvent", "0.0.1"));
-        final double rval = rand.nextGaussian();
-        triggerEvent.put("MonitoredValue", rval);
-        triggerEvent.put("LastMonitoredValue", 0D);
-        LOGGER.info("Triggering policy in Engine 1 with " + triggerEvent);
-        apexEngine1.handleEvent(triggerEvent);
-        final EnEvent result = listener1.getResult();
-        LOGGER.info("Receiving action event {} ", result);
-        assertEquals("ExecutionIDs are different", triggerEvent.getExecutionID(), result.getExecutionID());
-        triggerEvent.clear();
-        result.clear();
-        Thread.sleep(1);
-        apexEngine1.stop();
-    }
-
-    /**
-     * This policy passes, and receives a Double event context filed called "EVCDouble"<br>
-     * The policy tries to keep the value at 50, with a Min -100, Max 100 (These should probably be set using
-     * TaskParameters!)<br>
-     * The policy has 7 Decide Tasks that manipulate the value of this field in unknown ways.<br>
-     * The Decide TSL learns the effect of each task, and then selects the appropriate task to get the value back to
-     * 50<br>
-     * After the value settles close to 50 for a while, the test Rests the value to to random number and then
-     * continues<br>
-     * To plot the results grep stdout debug results for the string "*******", paste into excel and delete non-relevant
-     * columns<br>
-     *
-     * @throws ApexException the apex exception
-     * @throws InterruptedException the interrupted exception
-     * @throws IOException Signals that an I/O exception has occurred.
-     */
-    // @Test
-    public void TestAutoLearnTSL_main() throws ApexException, InterruptedException, IOException {
-
-        final double WANT = 50.0;
-        final double toleranceTileJump = 3.0;
-
-        final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAutoLearnPolicyModel();
-        assertNotNull(apexPolicyModel);
-
-        final AxValidationResult validationResult = new AxValidationResult();
-        apexPolicyModel.validate(validationResult);
-        assertTrue(validationResult.isValid());
-
-        final AxArtifactKey key = new AxArtifactKey("AADMApexEngine", "0.0.1");
-        final EngineParameters parameters = new EngineParameters();
-        parameters.getExecutorParameterMap().put("MVEL", new MVELExecutorParameters());
-        parameters.getExecutorParameterMap().put("JAVA", new JavaExecutorParameters());
-
-        final ApexEngine apexEngine1 = new ApexEngineFactory().createApexEngine(key);
-
-        final TestApexActionListener listener1 = new TestApexActionListener("TestListener1");
-        apexEngine1.addEventListener("listener1", listener1);
-        apexEngine1.updateModel(apexPolicyModel);
-        apexEngine1.start();
-
-        final EnEvent triggerEvent = apexEngine1.createEvent(new AxArtifactKey("AutoLearnTriggerEvent", "0.0.1"));
-        assertNotNull(triggerEvent);
-        final double MIN = -100;
-        final double MAX = 100;
-
-        double rval = (((rand.nextGaussian() + 1) / 2) * (MAX - MIN)) + MIN;
-        triggerEvent.put("MonitoredValue", rval);
-        triggerEvent.put("LastMonitoredValue", 0);
-
-        double avval = 0;
-        double distance;
-        double avcount = 0;
-
-        for (int iteration = 0; iteration < MAXITERATIONS; iteration++) {
-            // Trigger the policy in engine 1
-            LOGGER.info("Triggering policy in Engine 1 with " + triggerEvent);
-            apexEngine1.handleEvent(triggerEvent);
-            final EnEvent result = listener1.getResult();
-            LOGGER.info("Receiving action event {} ", result);
-            triggerEvent.clear();
-
-            double val = (Double) result.get("MonitoredValue");
-            final double prevval = (Double) result.get("LastMonitoredValue");
-
-            triggerEvent.put("MonitoredValue", prevval);
-            triggerEvent.put("LastMonitoredValue", val);
-
-            avcount = Math.min((avcount + 1), 20); // maintain average of only the last 20 values
-            avval = ((avval * (avcount - 1)) + val) / (avcount);
-
-            distance = Math.abs(WANT - avval);
-            if (distance < toleranceTileJump) {
-                rval = (((rand.nextGaussian() + 1) / 2) * (MAX - MIN)) + MIN;
-                val = rval;
-                triggerEvent.put("MonitoredValue", val);
-                LOGGER.info("Iteration " + iteration + ": Average " + avval + " has become closer (" + distance
-                        + ") than " + toleranceTileJump + " to " + WANT + " so reseting val:\t\t\t\t\t\t\t\t" + val);
-                avval = 0;
-                avcount = 0;
-            }
-            LOGGER.info("Iteration " + iteration + ": \tpreval\t" + prevval + "\tval\t" + val + "\tavval\t" + avval);
-
-            result.clear();
-            Thread.sleep(1);
-        }
-
-        apexEngine1.stop();
-        Thread.sleep(1000);
-
-    }
-
-    public static void main(final String[] args) throws ApexException, InterruptedException, IOException {
-        new TestAutoLearnTSLUseCase().TestAutoLearnTSL_main();
-    }
-}
diff --git a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/package-info.java b/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/package-info.java
deleted file mode 100644
index 0e004fe8d..000000000
--- a/examples/adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/package-info.java
+++ /dev/null
@@ -1,27 +0,0 @@
-/*-
- * ============LICENSE_START=======================================================
- *  Copyright (C) 2016-2018 Ericsson. All rights reserved.
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- * ============LICENSE_END=========================================================
- */
-
-/**
- * Defines domain and policies demonstrating adaptive policies.
- *
- * @author Liam Fallon (liam.fallon@ericsson.com)
- */
-
-package org.onap.policy.apex.examples.adaptive;
diff --git a/examples/adaptive/src/test/resources/META-INF/persistence.xml b/examples/adaptive/src/test/resources/META-INF/persistence.xml
deleted file mode 100644
index 7282bb562..000000000
--- a/examples/adaptive/src/test/resources/META-INF/persistence.xml
+++ /dev/null
@@ -1,69 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<!--
-  ============LICENSE_START=======================================================
-   Copyright (C) 2016-2018 Ericsson. All rights reserved.
-  ================================================================================
-  Licensed under the Apache License, Version 2.0 (the "License");
-  you may not use this file except in compliance with the License.
-  You may obtain a copy of the License at
-  
-       http://www.apache.org/licenses/LICENSE-2.0
-  
-  Unless required by applicable law or agreed to in writing, software
-  distributed under the License is distributed on an "AS IS" BASIS,
-  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-  See the License for the specific language governing permissions and
-  limitations under the License.
-  
-  SPDX-License-Identifier: Apache-2.0
-  ============LICENSE_END=========================================================
--->
-
-<persistence xmlns="http://java.sun.com/xml/ns/persistence" version="2.0">
-    <persistence-unit name="AdaptiveModelsTest" transaction-type="RESOURCE_LOCAL">
-        <provider>org.eclipse.persistence.jpa.PersistenceProvider</provider>
-
-        <class>org.onap.policy.apex.model.basicmodel.dao.converters.CDATAConditioner</class>
-        <class>org.onap.policy.apex.model.basicmodel.dao.converters.UUID2String</class>
-        <class>org.onap.policy.apex.model.basicmodel.concepts.AxArtifactKey</class>
-        <class>org.onap.policy.apex.model.basicmodel.concepts.AxConcept</class>
-        <class>org.onap.policy.apex.model.basicmodel.concepts.AxKeyInfo</class>
-        <class>org.onap.policy.apex.model.basicmodel.concepts.AxKeyInformation</class>
-        <class>org.onap.policy.apex.model.basicmodel.concepts.AxModel</class>
-        <class>org.onap.policy.apex.model.basicmodel.concepts.TestEntity</class>
-        <class>org.onap.policy.apex.model.contextmodel.concepts.AxContextSchema</class>
-        <class>org.onap.policy.apex.model.contextmodel.concepts.AxContextSchemas</class>
-        <class>org.onap.policy.apex.model.contextmodel.concepts.AxContextAlbum</class>
-        <class>org.onap.policy.apex.model.contextmodel.concepts.AxContextAlbums</class>
-        <class>org.onap.policy.apex.model.contextmodel.concepts.AxContextModel</class>
-        <class>org.onap.policy.apex.model.eventmodel.concepts.AxField</class>
-        <class>org.onap.policy.apex.model.eventmodel.concepts.AxInputField</class>
-        <class>org.onap.policy.apex.model.eventmodel.concepts.AxOutputField</class>
-        <class>org.onap.policy.apex.model.eventmodel.concepts.AxEvent</class>
-        <class>org.onap.policy.apex.model.eventmodel.concepts.AxEvents</class>
-        <class>org.onap.policy.apex.model.eventmodel.concepts.AxEventModel</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxLogic</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxTaskParameter</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxTaskLogic</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxTask</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxTasks</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxTaskSelectionLogic</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxStateFinalizerLogic</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxStateOutput</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxStateTaskReference</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxState</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxPolicy</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxPolicies</class>
-        <class>org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel</class>
-
-        <properties>
-            <property name="javax.persistence.jdbc.url" value="jdbc:derby:memory:apex_test" />
-            <property name="javax.persistence.target-database" value="Derby" />
-            <property name="javax.persistence.jdbc.driver" value="org.apache.derby.jdbc.EmbeddedDriver" />
-
-            <property name="eclipselink.ddl-generation" value="drop-and-create-tables" />
-            <property name="eclipselink.ddl-generation.output-mode" value="database" />
-            <property name="eclipselink.logging.level" value="INFO" />
-        </properties>
-    </persistence-unit>
-</persistence>