Practical Extensions of a Randomized Testing Tool
Date
2009
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IEEE
Abstract
Many efficient random testing algorithms for object-oriented software have been proposed due to their simplicity and reasonable code coverage; however, even the state-of-the-art random test algorithms yield very low code coverage (around 22%) on large-scale software. We propose four testing techniques to improve test coverage. The proposed techniques are pluggable to any existing random testing techniques for object-oriented software. We incorporated our techniques to
a state-of-the-art random testing tool and tested large-scale software, including Java Collections, Apache Ant, and ASM. Our experimental study shows that the proposed techniques increase at most 21% of branch coverage – a significant
improvement.
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Comments
This is a manuscript of a proceeding published as H. Jaygarl, C. K. Chang and S. Kim, "Practical Extensions of a Randomized Testing Tool," 2009 33rd Annual IEEE International Computer Software and Applications Conference, 2009, pp. 148-153, doi: 10.1109/COMPSAC.2009.29. Posted with permission.
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