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Proceedings of the 2015 IEEE International Conference on Software
Quality, Reliability and Security (QRS '15)
IEEE Computer Society Press, Los Alamitos, CA, pp. 131-140 (2015) |
Bo Jiang 2 , W.K. Chan 3 , and T.H. Tse 4
[paper from IEEE Xplore | paper from IEEE digital library | technical report TR-2015-07]
| ABSTRACT |
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Effective testing is essential for assuring software quality.
While regression testing is time-consuming,
the fault detection capability may be compromised if some test cases
are discarded.
Test case prioritization is a viable solution.
To the best of our knowledge,
the most effective test case prioritization approach is still the
additional greedy algorithm,
and existing search-based algorithms have been shown to be visually
less effective than the former algorithms in previous empirical studies.
This paper proposes a novel Proportion-Oriented Randomized Algorithm
(PORA) for test case prioritization.
PORA guides test case prioritization by optimizing the distance between
the prioritized test suite and a hierarchy of distributions of test
input data.
Our experiment shows that PORA test case prioritization techniques
are as effective as,
if not more effective than,
the total greedy,
additional greedy,
and ART techniques,
which use code coverage information.
Moreover, the experiment shows that PORA techniques are more stable
in effectiveness than the others.
Keywords: Test case prioritization, randomized algorithm, proportional sampling strategy, multi-objective optimization |
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