Mutation analysis has many applications, such as assessing the quality of test cases, fault localization, test input generation, security analysis, etc. Such applications involve running test suite against a large number of program mutants leading to poor scalability. Much research has been aimed at speeding up this process, focusing on reducing the number of mutants, the number of executed tests, or the execution time of the mutants. This paper presents a novel approach, named MeMu, for reducing the execution time of the mutants, by memoizing the most expensive methods in the system. Memoization is an optimization technique that allows bypassing the execution of expensive methods, when repeated inputs are detected. MeMu can be used in conjunction with existing acceleration techniques. We implemented MeMu on top of PITest, a well-known JVM bytecode-level mutation analysis system, and obtained, on average, an 18.15% speed-up over PITest, in the execution time of the mutants for 12 real-world programs. These promising results and the fact that MeMu could also be used for other applications that involve repeated execution of tests (e.g., automatic program repair and regression testing), strongly support future research for improving its efficiency.

中文翻译：

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致力于通过昂贵的方法加快突变分析

变异分析具有许多应用程序，例如评估测试用例的质量，故障定位，测试输入生成，安全性分析等。此类应用程序涉及针对大量程序变异体运行测试套件，从而导致可扩展性差。许多研究旨在加快这一过程，重点是减少突变体的数量，已执行测试的数量或突变体的执行时间。本文介绍了一种新颖的方法，称为MeMu，通过记录系统中最昂贵的方法来减少突变体的执行时间。记忆化是一种优化技术，当检测到重复输入时，可以绕过昂贵方法的执行。MeMu可以与现有的加速技术结合使用。我们在PITest之上实现了MeMu，一个著名的JVM字节码级突变分析系统，在12个真实程序的突变体执行时间上，平均速度比PITest高18.15％。这些有希望的结果以及MeMu还可以用于涉及重复执行测试（例如，自动程序修复和回归测试）的其他应用程序这一事实，有力地支持了提高效率的未来研究。