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Constructing subtle higher order mutants for Java and AspectJ programs

机译:为Java和AspectJ程序构造微妙的高阶突变体

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One goal of higher order mutation testing is to produce higher order mutants (HOMs) that represent subtle faults. We define subtle HOMs as those that are not killed by an existing test set that kills all the first order mutants of a given program. The fault detection effectiveness of the test set can be improved by adding test cases that kill subtle HOMs. However, finding subtle HOMs can be costly even for small programs because of the large space of candidate HOMs. Moreover, a large majority of HOMs are killed by test sets that kill all first order mutants, making the subtle ones relatively rare. We introduce three search-based algorithms (Genetic Algo-rithm, Local Search, and Random Search) for finding subtle HOMs in Java and AspectJ programs. All three algorithms found subtle HOMs for all studied programs but Local Search was more successful in finding subtle HOMs than Genetic Algorithm and Random Search.
机译:高阶突变测试的一个目标是生产代表细微缺陷的高阶突变体(HOM)。我们将细微的HOM定义为未被现有测试集杀死的HOM,该测试集杀死给定程序的所有一阶突变体。通过添加杀死微妙HOM的测试用例,可以提高测试集的故障检测效率。但是,由于候选HOM的空间很大,因此即使对于小型程序,查找细微的HOM也会很昂贵。此外,绝大多数HOM被杀死所有一阶突变体的测试集杀死,因此细微的HOM相对少见。我们介绍了三种基于搜索的算法(遗传算法,本地搜索和随机搜索),用于在Java和AspectJ程序中查找微妙的HOM。这三种算法都为所有研究程序找到了细微的HOM,但是与遗传算法和随机搜索相比,本地搜索在找到细微的HOM方面更为成功。

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