突变检测中的突变选择策略

Rowland Pitts
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引用次数: 0

摘要

突变测试提供了一种评估单元测试集质量的强大方法;然而,软件开发人员通常不愿意采用这种技术,因为它会产生大量的突变,包括冗余的和等效的突变。研究人员一直在寻求在不降低有效性的情况下减少突变体数量的策略,以及选择更有效突变体的方法,但没有一种策略比随机突变体选择表现得更好。由于等效突变体不能被杀死,使得突变充分性难以实现,因此大多数研究都假设未被杀死的突变体是等效的。使用15 java。对于已知具有真正足够突变的测试集的Lang类,本研究表明,即使等效突变的数量急剧减少,它们仍然是测试人员最大的问题,并且除了它们的存在之外,实现足够突变相对容易。它还评估了各种突变选择策略,并证明即使有足够的突变测试集,也没有一个比随机突变选择更有效。
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Mutant Selection Strategies in Mutation Testing
Mutation Testing offers a powerful approach to assessing unit test set quality; however, software developers are often reluctant to embrace the technique because of the tremendous number of mutants it generates, including redundant and equivalent mutants. Researchers have sought strategies to reduce the number of mutants without reducing effectiveness, and also ways to select more effective mutants, but no strategy has performed better than random mutant selection. Equivalent mutants, which cannot be killed, make achieving mutation adequacy difficult, so most research is conducted with the assumption that unkilled mutants are equivalent. Using 15 java.lang classes that are known to have truly mutation adequate test sets, this research demonstrates that even when the number of equivalent mutants is drastically reduced, they remain a tester's largest problem, and that apart from their presence achieving mutation adequacy is relatively easy. It also assesses a variety of mutant selection strategies and demonstrates that even with mutation adequate test sets, none perform as well as random mutant selection.
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