Initial sshsm project structure

Issue-ID: AAF-94
Change-Id: I5e82fff418e7567b161acf9b98013a9b85ffc5b4
Signed-off-by: NingSun <ning.sun@intel.com>

1 files changed, 144 insertions, 0 deletions

diff --git a/SoftHSMv2/src/lib/crypto/test/chisq.c b/SoftHSMv2/src/lib/crypto/test/chisq.c
new file mode 100644
index 0000000..3fe4f66
--- /dev/null
+++ b/SoftHSMv2/src/lib/crypto/test/chisq.c
@@ -0,0 +1,144 @@
+/* This code was taken from http://www.fourmilab.ch/random/ where it states that:
+
+   This software is in the public domain. Permission to use, copy, modify, and distribute 
+   this software and its documentation for any purpose and without fee is hereby granted, 
+   without any conditions or restrictions. This software is provided “as is” without 
+   express or implied warranty. */
+
+/*
+
+    Compute probability of measured Chi Square value.
+    
+    This code was developed by Gary Perlman of the Wang
+    Institute (full citation below) and has been minimally
+    modified for use in this program.
+    
+*/
+
+#include <math.h>
+
+/*HEADER
+	Module:       z.c
+	Purpose:      compute approximations to normal z distribution probabilities
+	Programmer:   Gary Perlman
+	Organization: Wang Institute, Tyngsboro, MA 01879
+	Copyright:    none
+	Tabstops:     4
+*/
+
+#define	Z_MAX          6.0            /* maximum meaningful z value */
+
+/*FUNCTION poz: probability of normal z value */
+/*ALGORITHM
+	Adapted from a polynomial approximation in:
+		Ibbetson D, Algorithm 209
+		Collected Algorithms of the CACM 1963 p. 616
+	Note:
+		This routine has six digit accuracy, so it is only useful for absolute
+		z values < 6.  For z values >= to 6.0, poz() returns 0.0.
+*/
+static double        /*VAR returns cumulative probability from -oo to z */
+poz(const double z)  /*VAR normal z value */
+{
+    double y, x, w;
+
+    if (z == 0.0) {
+    	x = 0.0;
+    } else {
+	y = 0.5 * fabs(z);
+	if (y >= (Z_MAX * 0.5)) {
+    	    x = 1.0;
+	} else if (y < 1.0) {
+	   w = y * y;
+	   x = ((((((((0.000124818987 * w
+		   -0.001075204047) * w +0.005198775019) * w
+		   -0.019198292004) * w +0.059054035642) * w
+		   -0.151968751364) * w +0.319152932694) * w
+		   -0.531923007300) * w +0.797884560593) * y * 2.0;
+	} else {
+	    y -= 2.0;
+	    x = (((((((((((((-0.000045255659 * y
+		    +0.000152529290) * y -0.000019538132) * y
+		    -0.000676904986) * y +0.001390604284) * y
+		    -0.000794620820) * y -0.002034254874) * y
+		    +0.006549791214) * y -0.010557625006) * y
+		    +0.011630447319) * y -0.009279453341) * y
+		    +0.005353579108) * y -0.002141268741) * y
+		    +0.000535310849) * y +0.999936657524;
+    	}
+    }
+    return (z > 0.0 ? ((x + 1.0) * 0.5) : ((1.0 - x) * 0.5));
+}
+
+/*
+	Module:       chisq.c
+	Purpose:      compute approximations to chisquare distribution probabilities
+	Contents:     pochisq()
+	Uses:         poz() in z.c (Algorithm 209)
+	Programmer:   Gary Perlman
+	Organization: Wang Institute, Tyngsboro, MA 01879
+	Copyright:    none
+	Tabstops:     4
+*/
+
+#define	LOG_SQRT_PI     0.5723649429247000870717135 /* log (sqrt (pi)) */
+#define	I_SQRT_PI       0.5641895835477562869480795 /* 1 / sqrt (pi) */
+#define	BIGX           20.0         /* max value to represent exp (x) */
+#define	ex(x)             (((x) < -BIGX) ? 0.0 : exp(x))
+
+/*FUNCTION pochisq: probability of chi sqaure value */
+/*ALGORITHM Compute probability of chi square value.
+	Adapted from:
+		Hill, I. D. and Pike, M. C.  Algorithm 299
+		Collected Algorithms for the CACM 1967 p. 243
+	Updated for rounding errors based on remark in
+		ACM TOMS June 1985, page 185
+*/
+
+double pochisq(
+    	const double ax,    /* obtained chi-square value */
+     	const int df	    /* degrees of freedom */
+     	)
+{
+    double x = ax;
+    double a, y, s;
+    double e, c, z;
+    int even;	    	    /* true if df is an even number */
+
+    if (x <= 0.0 || df < 1) {
+    	return 1.0;
+    }
+
+    a = 0.5 * x;
+    even = (2 * (df / 2)) == df;
+    y = 0.0;
+    if (df > 1) {
+    	y = ex(-a);
+    }
+    s = (even ? y : (2.0 * poz(-sqrt(x))));
+    if (df > 2) {
+	x = 0.5 * (df - 1.0);
+	z = (even ? 1.0 : 0.5);
+	if (a > BIGX) {
+    	    e = (even ? 0.0 : LOG_SQRT_PI);
+    	    c = log(a);
+    	    while (z <= x) {
+		e = log(z) + e;
+		s += ex(c * z - a - e);
+		z += 1.0;
+    	    }
+    	    return (s);
+    	} else {
+	    e = (even ? 1.0 : (I_SQRT_PI / sqrt(a)));
+	    c = 0.0;
+	    while (z <= x) {
+		    e = e * (a / z);
+		    c = c + e;
+		    z += 1.0;
+    	    }
+	    return (c * y + s);
+    	}
+    } else {
+    	return s;
+    }
+}