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Correlating automatic static analysis and mutation testing: towards incremental strategies

机译:关联自动静态分析和变异测试:逐步实现策略

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Abstract Background Traditionally, mutation testing is used as test set generation and/or test evaluation criteria once it is considered a good fault model. This paper uses mutation testing for evaluating an automated static analyzer. Since static analyzers, in general, report a substantial number of false positive warnings, the intention of this study is to define a prioritization approach of static warnings based on their correspondence with mutations. On the other hand, knowing that Mutation Test has a high application cost, another possibility is to try to identify mutations of some specific mutation operators, which an automatic static analyzer is not adequate to detect. Therefore, this information can be used to prioritize the order of incrementally applying mutation operators considering, firstly, those with no correspondence with static warnings. In both cases, contributing to the establishment of incremental strategies on using automatic static analysis or mutation testing or even a combination of them. Methods We used mutation operators as a fault model to evaluate the direct correspondence between mutations and static warnings. The main advantage of using mutation operators is that they generate a large number of programs containing faults of different types, which can be used to decide the ones most probable to be detected by static analyzers. Results We provide evidences on the correspondence between mutations and some types of static warnings. The results obtained for a set of 19 open-source programs indicate that: 1) static warnings may be prioritized based on their correspondence level with mutations; 2) specific set of mutation operators and their mutations may be prioritized based on their correspondence level with warnings. Conclusion It is possible to provide an incremental testing strategy aiming at reducing the cost of both static analysis and mutation testing using the correspondence information between these activities/artifacts.
机译:抽象背景传统上,一旦被认为是好的故障模型,就将变异测试用作测试集生成和/或测试评估标准。本文使用突变测试来评估自动静态分析仪。由于静态分析器通常会报告大量的误报,因此,本研究的目的是基于静态警告与突变的对应关系来定义优先级排序方法。另一方面,了解突变测试具有较高的应用成本,另一种可能性是尝试识别某些特定的突变算子,而自动静态分析仪不足以检测这种变异。因此,该信息可用于优先考虑与静态警告不对应的变异算子的递增应用变异算子的顺序。在这两种情况下,都有助于建立使用自动静态分析或突变测试甚至是它们的组合的增量策略。方法我们使用变异算子作为故障模型来评估变异与静态警告之间的直接对应关系。使用变异算子的主要优点是,它们会生成大量包含不同类型故障的程序,这些程序可用于确定最有可能被静态分析仪检测到的程序。结果我们提供了突变与某些类型的静态警告之间的对应关系的证据。从一组19个开源程序获得的结果表明:1)静态警告可以根据它们与突变的对应程度来优先处理; 2)特定的一组突变算子及其突变可以根据其与警告的对应程度来优先处理。结论可以使用这些活动/工件之间的对应信息,提供旨在降低静态分析和突变测试成本的增量测试策略。

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