From 79e389f4318fa7b729d52363cd3566e477f7691e Mon Sep 17 00:00:00 2001
From: David Garcia Quintas <dgq@google.com>
Date: Tue, 2 Jun 2015 17:49:42 -0700
Subject: [PATCH] Improvements to the way we randomize test runs.

---
 tools/run_tests/jobset.py    | 40 ------------------------------------
 tools/run_tests/run_tests.py | 22 +++++++++++++-------
 2 files changed, 15 insertions(+), 47 deletions(-)

diff --git a/tools/run_tests/jobset.py b/tools/run_tests/jobset.py
index 51d61db7f6c..985b7a7f165 100755
--- a/tools/run_tests/jobset.py
+++ b/tools/run_tests/jobset.py
@@ -33,7 +33,6 @@ import hashlib
 import multiprocessing
 import os
 import platform
-import random
 import signal
 import subprocess
 import sys
@@ -59,40 +58,6 @@ else:
   signal.signal(signal.SIGALRM, alarm_handler)
 
 
-def shuffle_iteratable(it):
-  """Return an iterable that randomly walks it"""
-  # take a random sampling from the passed in iterable
-  # we take an element with probability 1/p and rapidly increase
-  # p as we take elements - this gives us a somewhat random set of values before
-  # we've seen all the values, but starts producing values without having to
-  # compute ALL of them at once, allowing tests to start a little earlier
-  LARGE_THRESHOLD = 1000
-  nextit = []
-  p = 1
-  for val in it:
-    if random.randint(0, p) == 0:
-      p = min(p*2, 100)
-      yield val
-    else:
-      nextit.append(val)
-      # if the input iterates over a large number of values (potentially
-      # infinite, we'd be in the loop for a while (again, potentially forever).
-      # We need to reset "nextit" every so often to, in the case of an infinite
-      # iterator, avoid growing "nextit" without ever freeing it.
-      if len(nextit) > LARGE_THRESHOLD:
-        random.shuffle(nextit)
-        for val in nextit:
-          yield val
-        nextit = []
-        p = 1
-
-  # after taking a random sampling, we shuffle the rest of the elements and
-  # yield them
-  random.shuffle(nextit)
-  for val in nextit:
-    yield val
-
-
 _SUCCESS = object()
 _FAILURE = object()
 _RUNNING = object()
@@ -358,11 +323,6 @@ def run(cmdlines,
               maxjobs if maxjobs is not None else _DEFAULT_MAX_JOBS,
               newline_on_success, travis, stop_on_failure,
               cache if cache is not None else NoCache())
-  # We can't sort an infinite sequence of runs.
-  if not travis or infinite_runs:
-    cmdlines = shuffle_iteratable(cmdlines)
-  else:
-    cmdlines = sorted(cmdlines, key=lambda x: x.shortname)
   for cmdline in cmdlines:
     if not js.start(cmdline):
       break
diff --git a/tools/run_tests/run_tests.py b/tools/run_tests/run_tests.py
index c00d7941f44..32405675b6b 100755
--- a/tools/run_tests/run_tests.py
+++ b/tools/run_tests/run_tests.py
@@ -36,16 +36,16 @@ import itertools
 import json
 import multiprocessing
 import os
+import platform
+import random
 import re
+import subprocess
 import sys
 import time
-import platform
-import subprocess
 
 import jobset
 import watch_dirs
 
-
 ROOT = os.path.abspath(os.path.join(os.path.dirname(sys.argv[0]), '../..'))
 os.chdir(ROOT)
 
@@ -488,13 +488,21 @@ def _build_and_run(check_cancelled, newline_on_success, travis, cache):
     return 1
 
   # start antagonists
-  antagonists = [subprocess.Popen(['tools/run_tests/antagonist.py']) 
+  antagonists = [subprocess.Popen(['tools/run_tests/antagonist.py'])
                  for _ in range(0, args.antagonists)]
   try:
     infinite_runs = runs_per_test == 0
-    # run all the tests
-    runs_sequence = (itertools.repeat(one_run) if infinite_runs
-                     else itertools.repeat(one_run, runs_per_test))
+    # When running on travis, we want out test runs to be as similar as possible
+    # for reproducibility purposes.
+    if travis:
+      massaged_one_run = sorted(one_run, key=lambda x: x.shortname)
+    else:
+      # whereas otherwise, we want to shuffle things up to give all tests a
+      # chance to run.
+      massaged_one_run = list(one_run)  # random.shuffle needs an indexable seq.
+      random.shuffle(massaged_one_run)  # which it modifies in-place.
+    runs_sequence = (itertools.repeat(massaged_one_run) if infinite_runs
+                     else itertools.repeat(massaged_one_run, runs_per_test))
     all_runs = itertools.chain.from_iterable(runs_sequence)
     if not jobset.run(all_runs, check_cancelled,
                       newline_on_success=newline_on_success, travis=travis,