Faster mutation analysis with MeMu

Ali Ghanbari, Andrian Marcus
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引用次数: 1

Abstract

Mutation analysis is a program analysis method with applications in assessing the quality of test cases, fault localization, test input generation, security analysis, etc. The method involves repeated running of test suites against a large number of program mutants, often leading to poor scalability. A large body of research is aimed at accelerating mutation analysis via a variety of approaches such as, reducing the number of mutants, reducing the number of test cases to run, or reducing the execution time of individual mutants. This paper presents the implementation of a novel technique, named MeMu, for reducing mutant execution time, through memoizing the most expensive methods in the system. Memoization is a program optimization technique that allows bypassing the execution of expensive methods and reusing pre-calculated results, when repeated inputs are detected. MeMu can be used on its own or alongside existing mutation analysis acceleration techniques. The current implementation of MeMu achieves, on average, an 18.15% speed-up for PITest JVM-based mutation testing tool.
使用MeMu进行更快的突变分析
突变分析是一种应用于测试用例质量评估、故障定位、测试输入生成、安全性分析等方面的程序分析方法。该方法涉及针对大量程序突变重复运行测试套件,通常导致较差的可伸缩性。大量的研究旨在通过各种方法加速突变分析,例如减少突变的数量,减少要运行的测试用例的数量,或者减少单个突变的执行时间。本文介绍了一种名为MeMu的新技术的实现,通过记忆系统中最昂贵的方法来减少突变的执行时间。记忆是一种程序优化技术,当检测到重复输入时,它允许绕过昂贵方法的执行并重用预先计算的结果。MeMu可以单独使用,也可以与现有的突变分析加速技术一起使用。对于基于jvm的PITest突变测试工具,MeMu的当前实现平均实现了18.15%的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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