Evaluating Non-Adequate Test-Case Reduction

ASE(2016)

引用 36|浏览110
暂无评分
摘要
Given two test cases, one larger and one smaller, the smaller test case is preferred for many purposes. A smaller test case usually runs faster, is easier to understand, and is more convenient for debugging. However, smaller test cases also tend to cover less code and detect fewer faults than larger test cases. Whereas traditional research focused on reducing test suites while preserving code coverage, recent work has introduced the idea of reducing individual test cases, rather than test suites, while still preserving code coverage. Other recent work has proposed non-adequately reducing test suites by not even preserving all the code coverage. This paper empirically evaluates a new combination of these two ideas, non-adequate reduction of test cases, which allows for a wide range of trade-offs between test case size and fault detection.Our study introduces and evaluates C%-coverage reduction (where a test case is reduced to retain at least C% of its original coverage) and N-mutant reduction (where a test case is reduced to kill at least N of the mutants it originally killed). We evaluate the reduction trade-offs with varying values of C% and N for four real-world C projects: Mozilla's SpiderMonkey JavaScript engine, the YAFFS2 flash file system, Grep, and Gzip. The results show that it is possible to greatly reduce the size of many test cases while still preserving much of their fault-detection capability.
更多
查看译文
关键词
test reduction,test adequacy,coverage,mutation testing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要