Seattle Conference on Scalability: Scalable Test Selection Using Source Code
40:09
-
2 years ago
Google Tech Talks
June 23, 2007
ABSTRACT
2007 Google Seattle Conference on Scalability:
Scalable Test Selection Using Source Code Deltas
Speaker: Ryan Gerard, Symantec Corporation
As the number of automated regression tests increase, the ability to
run all of them in a reasonable amount of time becomes more and
more difficult, and simply doesn't scale. Since we are looking for
regressions, it is useful to hone in on the parts of the code that have
changed from the last run to help select a small subset of tests that
are likely to find the regression. In this way we are only running the
tests that need to be run as your system gets larger and the number
of possible tests scales outward. We have devised a method to
select a subset of tests from an existing test set for scalable
regression testing based on source code changes, or deltas. The
selection algorithm is a static data mining technique that establishes
the relationship between source code deltas and test case
execution results. Test selection is then based on the established
correlation. In this talk, we will discuss the benefits and also the
pitfalls involved in having such an infrastructure. Finally, we will talk
about how best to add it to a nightly or continuous test automation
infrastructure.
Ryan Gerard is currently an SQA Engineer at Symantec. He has a
BS in Computer Science and Engineering from UCLA, and is
currently pursuing his MS in Information Security. Ryan’s particular
specialties are in web technologies and security testing, although
his interests span kernel-level technologies to process
improvements to data analysis.Google Tech Talks
June 23, 2007
ABSTRACT
2007 Google Seattle Conference on Scalability:
Scalable Test Selection Using Source Code De...all »Google Tech Talks
June 23, 2007
ABSTRACT
2007 Google Seattle Conference on Scalability:
Scalable Test Selection Using Source Code Deltas
Speaker: Ryan Gerard, Symantec Corporation
As the number of automated regression tests increase, the ability to
run all of them in a reasonable amount of time becomes more and
more difficult, and simply doesn't scale. Since we are looking for
regressions, it is useful to hone in on the parts of the code that have
changed from the last run to help select a small subset of tests that
are likely to find the regression. In this way we are only running the
tests that need to be run as your system gets larger and the number
of possible tests scales outward. We have devised a method to
select a subset of tests from an existing test set for scalable
regression testing based on source code changes, or deltas. The
selection algorithm is a static data mining technique that establishes
the relationship between source code deltas and test case
execution results. Test selection is then based on the established
correlation. In this talk, we will discuss the benefits and also the
pitfalls involved in having such an infrastructure. Finally, we will talk
about how best to add it to a nightly or continuous test automation
infrastructure.
Ryan Gerard is currently an SQA Engineer at Symantec. He has a
BS in Computer Science and Engineering from UCLA, and is
currently pursuing his MS in Information Security. Ryan’s particular
specialties are in web technologies and security testing, although
his interests span kernel-level technologies to process
improvements to data analysis.«
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