Add cross-platform randomizer module.

The code uses two mechanisms for generating random numbers: srand()/rand(),
which is not thread-safe, and srandom()/random(), which is POSIX-specific.

Here I add a util/random.cc module that centralizes these calls, and unifies
some common usage patterns.  If the implementation is not good enough, we can
now change it in a single place.

To keep things simple, this uses the portable srand()/rand() but protects them
with a lock to avoid concurrency problems.

The hard part was to keep the regression tests passing: they rely on fixed
sequences of random numbers, so a small code change could break them very
thoroughly.  Util::rand(), for wide types like size_t, calls std::rand() not
once but twice.  This behaviour was generalized into utils::wide_rand() and
friends.

1 files changed, 3 insertions, 3 deletions

diff --git a/mert/evaluator.cpp b/mert/evaluator.cpp
index 61775a354..59ffaf3cd 100644
--- a/mert/evaluator.cpp
+++ b/mert/evaluator.cpp
@@ -95,7 +95,7 @@ void EvaluatorUtil::evaluate(const string& candFile, int bootstrap, bool nbest_i
     for (int i = 0; i < bootstrap; ++i) {
       ScoreData scoredata(g_scorer);
       for (int j = 0; j < n; ++j) {
-        int randomIndex = util::rand_int() % n;
+        const int randomIndex = util::rand_excl(n);
         scoredata.add(entries[randomIndex], j);
       }
       g_scorer->setScoreData(&scoredata);
@@ -285,10 +285,10 @@ void InitSeed(const ProgramOption *opt)
 {
   if (opt->has_seed) {
     cerr << "Seeding random numbers with " << opt->seed << endl;
-    util::rand_int_init(opt->seed);
+    util::rand_init(opt->seed);
   } else {
     cerr << "Seeding random numbers with system clock " << endl;
-    util::rand_int_init();
+    util::rand_init();
   }
 }