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An experimental and practical study on the equivalent mutant connection: An evolutionary approach

机译:对等效突变角度的实验与实践研究:一种进化方法

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Context: Mutation testing is considered to be a powerful approach to assess and improve the quality of test suites. However, this technique is expensive mainly because some mutants are semantically equivalent to the original program; in general, equivalent mutants require manual revision to differentiate them from useful ones, which is known as the Equivalent Mutant Problem (EMP).Objective: In the past, several authors have proposed different techniques to individually identify certain equivalent mutants, with notable advances in the last years. In our work, by contrast, we address the EMP from a global perspective. Namely, we wonder the extent to which equivalent mutants are connected (i.e., whether they share mutation operators and code areas) as well as the extent to which the knowledge of that connection can benefit the mutant selection process. Such a study could allow going beyond the implicit limit in the traditional individual detection of equivalent mutants.Method: We use an evolutionary algorithm to select the mutants, an approach called Evolutionary Mutation Testing (EMT). We propose a new derived version, Equivalence-Aware EMT (EA-EMT), which penalizes the fitness of known equivalent mutants so that they do not transfer their features to the next generations of mutants.Results: In our experiments applying EMT to well-known C++ programs, we found that (i) equivalent mutants often originate from other equivalent mutants (over 60% on average); (H) EA-EMT's approach of penalizing known equivalent mutants provides better results than the original EMT in most of the cases (notably, the more equivalent mutants are detected, the better); and (Hi) we can combine EA-EMT with Trivial Compiler Equivalence as a way to automatically identify equivalent mutants in a real situation, reaching a more stable version of EMT.Conclusions: This novel approach opens the way for improvement in other related areas that deal with equivalent versions.
机译:背景:突变测试被认为是评估和提高测试套件质量的强大方法。然而,这种技术主要是因为某些突变体是语义上等同于原始程序的级数;通常,等效突变体需要手动修订,以将它们与有用的突变体分化为相当于突变问题(EMP)。目的:在过去,有几位作者提出了单独识别某些等效突变体的不同技术,具有显着的进步过去几年。相比之下,在我们的工作中,我们将EMP从全球范围内解决。即,我们想知道等效突变体连接的程度(即它们是否共享突变运营商和代码区域)以及该连接的知识可以使突变选择过程有益的程度。这种研究可以允许超出传统个体检测的等效突变体的隐含极限。方法:我们使用进化算法选择突变体,一种称为进化突变测试(EMT)的方法。我们提出了一个新的派生版本,等效感知EMT(EA-EMT),其惩罚了已知的等同突变体的适应性,以便它们不会将它们的特征转移到下一代突变体。结果:在我们的实验中申请EMT的实验 - 已知的C ++程序,我们发现(i)等效突变体通常来自其他等同突变体(平均超过60%); (h)EA-EMT惩罚着名的等效突变体的方法提供比原始EMT在大多数情况下的更好的结果(特别是,检测到更等量的突变体,更好); (嗨)我们可以将EA-EMT与琐碎的编译器等价相结合,以便在真实情况下自动识别等效突变体,达到更稳定的EMT版本:这种新颖的方法为其他相关领域开辟了改进的方式处理等效版本。

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