mirror of
https://github.com/openssl/openssl.git
synced 2024-11-27 05:21:51 +08:00
Test of uniformity of BN_rand_range output.
Rework the test so that it fails far less often. A number of independent tests are executed and 5% are expected to fail. The number of such failures follows a binomial distribution which permits a statistical test a 0.01% expected failure rate. There is a command line option to enable the stochastic range checking. It is off by default. Reviewed-by: Matt Caswell <matt@openssl.org> (Merged from https://github.com/openssl/openssl/pull/8830)
This commit is contained in:
Pauli
parent
d4e2d5db62
commit
5d2f3e4a6c
5
INSTALL
5
INSTALL
@ -1200,6 +1200,11 @@
|
||||
|
||||
$ make TESTS='[89]? -90'
|
||||
|
||||
To stochastically verify that the algorithm that produces uniformly distributed
|
||||
random numbers is operating correctly (with a false positive rate of 0.01%):
|
||||
|
||||
$ ./util/shlib_wrap.sh test/bntest -stochastic
|
||||
|
||||
Note on multi-threading
|
||||
-----------------------
|
||||
|
||||
|
||||
58
test/bn_rand_range.h
Normal file
58
test/bn_rand_range.h
Normal file
@ -0,0 +1,58 @@
|
||||
/*
|
||||
* WARNING: do not edit!
|
||||
* Generated by statistics/bn_rand_range.py in the OpenSSL tool repository.
|
||||
*
|
||||
* Copyright 2019 The OpenSSL Project Authors. All Rights Reserved.
|
||||
*
|
||||
* Licensed under the Apache License 2.0 (the "License"). You may not use
|
||||
* this file except in compliance with the License. You can obtain a copy
|
||||
* in the file LICENSE in the source distribution or at
|
||||
* https://www.openssl.org/source/license.html
|
||||
*/
|
||||
|
||||
static const struct {
|
||||
unsigned int range;
|
||||
unsigned int iterations;
|
||||
double critical;
|
||||
} rand_range_cases[] = {
|
||||
{ 2, 200, 3.841459 },
|
||||
{ 3, 300, 5.991465 },
|
||||
{ 4, 400, 7.814728 },
|
||||
{ 5, 500, 9.487729 },
|
||||
{ 6, 600, 11.070498 },
|
||||
{ 7, 700, 12.591587 },
|
||||
{ 8, 800, 14.067140 },
|
||||
{ 9, 900, 15.507313 },
|
||||
{ 10, 1000, 16.918978 },
|
||||
{ 11, 1100, 18.307038 },
|
||||
{ 12, 1200, 19.675138 },
|
||||
{ 13, 1300, 21.026070 },
|
||||
{ 14, 1400, 22.362032 },
|
||||
{ 15, 1500, 23.684791 },
|
||||
{ 16, 1600, 24.995790 },
|
||||
{ 17, 1700, 26.296228 },
|
||||
{ 18, 1800, 27.587112 },
|
||||
{ 19, 1900, 28.869299 },
|
||||
{ 20, 2000, 30.143527 },
|
||||
{ 30, 3000, 42.556968 },
|
||||
{ 40, 4000, 54.572228 },
|
||||
{ 50, 5000, 66.338649 },
|
||||
{ 60, 6000, 77.930524 },
|
||||
{ 70, 7000, 89.391208 },
|
||||
{ 80, 8000, 100.748619 },
|
||||
{ 90, 9000, 112.021986 },
|
||||
{ 100, 10000, 123.225221 },
|
||||
{ 1000, 10000, 1073.642651 },
|
||||
{ 2000, 20000, 2104.128222 },
|
||||
{ 3000, 30000, 3127.515432 },
|
||||
{ 4000, 40000, 4147.230012 },
|
||||
{ 5000, 50000, 5164.598069 },
|
||||
{ 6000, 60000, 6180.299514 },
|
||||
{ 7000, 70000, 7194.738181 },
|
||||
{ 8000, 80000, 8208.177159 },
|
||||
{ 9000, 90000, 9220.799176 },
|
||||
{ 10000, 100000, 10232.737266 },
|
||||
};
|
||||
|
||||
static const int binomial_critical = 29;
|
||||
|
||||
@ -1956,25 +1956,27 @@ static int test_rand(void)
|
||||
|
||||
/*
|
||||
* Run some statistical tests to provide a degree confidence that the
|
||||
* BN_rand_range() function works as expected. The critical value
|
||||
* is computed using the R statistical suite:
|
||||
* BN_rand_range() function works as expected. The test cases and
|
||||
* critical values are generated by the bn_rand_range script.
|
||||
*
|
||||
* qchisq(alpha, df=iterations - 1)
|
||||
* Each individual test is a Chi^2 goodness of fit for a specified number
|
||||
* of samples and range. The samples are assumed to be independent and
|
||||
* that they are from a discrete uniform distribution.
|
||||
*
|
||||
* where alpha is the significance level (0.95 is used here) and iterations
|
||||
* is the number of samples being drawn.
|
||||
* Some of these individual tests are expected to fail, the success/failure
|
||||
* of each is an independent Bernoulli trial. The number of such successes
|
||||
* will form a binomial distribution. The count of the successes is compared
|
||||
* against a precomputed critical value to determine the overall outcome.
|
||||
*/
|
||||
static const struct {
|
||||
struct rand_range_case {
|
||||
unsigned int range;
|
||||
unsigned int iterations;
|
||||
double critical;
|
||||
} rand_range_cases[] = {
|
||||
{ 2, 100, 123.2252 /* = qchisq(.95, df=99) */ },
|
||||
{ 12, 1000, 1073.643 /* = qchisq(.95, df=999) */ },
|
||||
{ 1023, 100000, 100735.7 /* = qchisq(.95, df=99999) */ },
|
||||
};
|
||||
|
||||
static int test_rand_range(int n)
|
||||
#include "bn_rand_range.h"
|
||||
|
||||
static int test_rand_range_single(size_t n)
|
||||
{
|
||||
const unsigned int range = rand_range_cases[n].range;
|
||||
const unsigned int iterations = rand_range_cases[n].iterations;
|
||||
@ -1998,22 +2000,20 @@ static int test_rand_range(int n)
|
||||
counts[v]++;
|
||||
}
|
||||
|
||||
TEST_note("range %u iterations %u critical %.4f", range, iterations,
|
||||
critical);
|
||||
if (range < 20) {
|
||||
TEST_note("frequencies (expected %.2f)", expected);
|
||||
for (i = 0; i < range; i++)
|
||||
TEST_note(" %2u %6zu", i, counts[i]);
|
||||
}
|
||||
for (i = 0; i < range; i++) {
|
||||
const double delta = counts[i] - expected;
|
||||
sum += delta * delta;
|
||||
}
|
||||
sum /= expected;
|
||||
TEST_note("test statistic %.4f", sum);
|
||||
|
||||
if (TEST_double_lt(sum, critical))
|
||||
res = 1;
|
||||
if (sum > critical) {
|
||||
TEST_info("Chi^2 test negative %.4f > %4.f", sum, critical);
|
||||
TEST_note("test case %zu range %u iterations %u", n + 1, range,
|
||||
iterations);
|
||||
goto err;
|
||||
}
|
||||
|
||||
res = 1;
|
||||
err:
|
||||
BN_free(rng);
|
||||
BN_free(val);
|
||||
@ -2021,6 +2021,19 @@ err:
|
||||
return res;
|
||||
}
|
||||
|
||||
static int test_rand_range(void)
|
||||
{
|
||||
int n_success = 0;
|
||||
size_t i;
|
||||
|
||||
for (i = 0; i < OSSL_NELEM(rand_range_cases); i++)
|
||||
n_success += test_rand_range_single(i);
|
||||
if (TEST_int_ge(n_success, binomial_critical))
|
||||
return 1;
|
||||
TEST_note("This test is expeced to fail by chance 0.01%% of the time.");
|
||||
return 0;
|
||||
}
|
||||
|
||||
static int test_negzero(void)
|
||||
{
|
||||
BIGNUM *a = NULL, *b = NULL, *c = NULL, *d = NULL;
|
||||
@ -2448,11 +2461,18 @@ static int run_file_tests(int i)
|
||||
return c == 0;
|
||||
}
|
||||
|
||||
typedef enum OPTION_choice {
|
||||
OPT_ERR = -1,
|
||||
OPT_EOF = 0,
|
||||
OPT_STOCHASTIC_TESTS,
|
||||
OPT_TEST_ENUM
|
||||
} OPTION_CHOICE;
|
||||
|
||||
const OPTIONS *test_get_options(void)
|
||||
{
|
||||
enum { OPT_TEST_ENUM };
|
||||
static const OPTIONS test_options[] = {
|
||||
OPT_TEST_OPTIONS_WITH_EXTRA_USAGE("[file...]\n"),
|
||||
{ "stochastic", OPT_STOCHASTIC_TESTS, '-', "Run stochastic tests" },
|
||||
{ OPT_HELP_STR, 1, '-',
|
||||
"file\tFile to run tests on. Normal tests are not run\n" },
|
||||
{ NULL }
|
||||
@ -2462,7 +2482,22 @@ const OPTIONS *test_get_options(void)
|
||||
|
||||
int setup_tests(void)
|
||||
{
|
||||
int n = test_get_argument_count();
|
||||
OPTION_CHOICE o;
|
||||
int n, stochastic = 0;
|
||||
|
||||
while ((o = opt_next()) != OPT_EOF) {
|
||||
switch (o) {
|
||||
case OPT_STOCHASTIC_TESTS:
|
||||
stochastic = 1;
|
||||
break;
|
||||
case OPT_TEST_CASES:
|
||||
break;
|
||||
default:
|
||||
case OPT_ERR:
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
n = test_get_argument_count();
|
||||
|
||||
if (!TEST_ptr(ctx = BN_CTX_new()))
|
||||
return 0;
|
||||
@ -2499,7 +2534,8 @@ int setup_tests(void)
|
||||
#endif
|
||||
ADD_ALL_TESTS(test_is_prime, (int)OSSL_NELEM(primes));
|
||||
ADD_ALL_TESTS(test_not_prime, (int)OSSL_NELEM(not_primes));
|
||||
ADD_ALL_TESTS(test_rand_range, OSSL_NELEM(rand_range_cases));
|
||||
if (stochastic)
|
||||
ADD_TEST(test_rand_range);
|
||||
} else {
|
||||
ADD_ALL_TESTS(run_file_tests, n);
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user