Apache::TestSmoke(3)  User Contributed Perl Documentation Apache::TestSmoke(3)

       Apache::TestSmoke - Special Tests Sequence Failure Finder

         # get the usage and the default values
         % t/SMOKE -help

         # repeat all tests 5 times and try 20 random iterations
         # and save the report into the file 'myreport'
         % t/SMOKE -times=5 -iterations=20 -report=myreport

         # run all tests default number of iterations, and repeat tests
         # default number of times
         % t/SMOKE

         # same as above but work only the specified tests
         % t/SMOKE foo/bar foo/tar

         # run once a sequence of tests in a non-random mode
         # e.g. when trying to reduce a known long sequence that fails
         % t/SMOKE -order=rotate -times=1 foo/bar foo/tar

         # now read the created report file

       The Problem

       When we try to test a stateless machine (i.e. all tests are indepen-
       dent), running all tests once ensures that all tested things properly
       work. However when a state machine is tested (i.e. where a run of one
       test may influence another test) it's not enough to run all the tests
       once to know that the tested features actually work. It's quite possi-
       ble that if the same tests are run in a different order and/or repeated
       a few times, some tests may fail.  This usually happens when some tests
       don't restore the system under test to its pristine state at the end of
       the run, which may influence other tests which rely on the fact that
       they start on pristine state, when in fact it's not true anymore. In
       fact it's possible that a single test may fail when run twice or three
       times in a sequence.

       The Solution

       To reduce the possibility of such dependency errors, it's important to
       run random testing repeated many times with many different srand seeds.
       Of course if no failures get spotted that doesn't mean that there are
       no tests inter-dependencies, which may cause a failure in production.
       But random testing definitely helps to spot many problems and gives
       better test coverage.

       Resolving Sequence Problems

       When this kind of testing is used and a failure is detected there are
       two problems:

       1   First is to be able to reproduce the problem so if we think we
           fixed it, we could verify the fix. This one is easy, just remember
           the sequence of tests run till the failed test and rerun the same
           sequence once again after the problem has been fixed.

       2   Second is to be able to understand the cause of the problem. If
           during the random test the failure has happened after running 400
           tests, how can we possibly know which previously running tests has
           caused to the failure of the test 401. Chances are that most of the
           tests were clean and don't have inter-dependency problem. Therefore
           it'd be very helpful if we could reduce the long sequence to a min-
           imum. Preferably 1 or 2 tests. That's when we can try to understand
           the cause of the detected problem.

       This utility attempts to solve both problems, and at the end of each
       iteration print a minimal sequence of tests causing to a failure. This
       doesn't always succeed, but works in many cases.

       This utility:

       1   Runs the tests randomly until the first failure is detected. Or
           non-randomly if the option -order is set to repeat or rotate.

       2   Then it tries to reduce that sequence of tests to a minimum, and
           this sequence still causes to the same failure.

       3   (XXX: todo): then it reruns the minimal sequence in the verbose
           mode and saves the output.

       4   It reports all the successful reductions as it goes to STDOUT and
           report file of the format: smoke-report-<date>.txt.

           In addition the systems build parameters are logged into the report
           file, so the detected problems could be reproduced.

       5   Goto 1 and run again using a new random seed, which potentially
           should detect different failures.

Reduction Algorithm
       Currently for each reduction path, the following reduction algorithms
       get applied:

       1   Binary search: first try the upper half then the lower.

       2   Random window: randomize the left item, then the right item and
           return the items between these two points.

       t/SMOKE.PL is driving this module, if you don't have it, create it:


         use strict;
         use warnings FATAL => 'all';

         use FindBin;
         use lib "$FindBin::Bin/../Apache-Test/lib";
         use lib "$FindBin::Bin/../lib";

         use Apache::TestSmoke ();


       usually Makefile.PL converts it into t/SMOKE while adjusting the perl
       path, but you create t/SMOKE in first place as well.

       Stas Bekman

perl v5.8.0                       2002-05-14              Apache::TestSmoke(3)