AutoMR: Automatic Discovery and Cleansing of Numerical Metamorphic Relations

Bo Zhang, Hongyu Zhang, Junjie Chen, Dan Hao, P. Moscato
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引用次数: 1

Abstract

This artifact is related to our Research Track paper that is accepted at ICSME 2019 [1]. Metamorphic relations (MRs) describe the invariant relationships between program inputs and outputs. We propose AutoMR, a novel method for systematically inferring and cleansing MRs. AutoMR can discover various types of equality and inequality MRs through a search method (particle swarm optimization). It also employs matrix singular-value decomposition and constraint solving techniques to remove the redundant MRs in the search results. Our experiments on 37 numerical programs show that AutoMR can effectively infer accurate and succinct MRs and outperform the state-of-the-art method. Furthermore, we show that the discovered MRs have high fault detection ability in mutation testing and differential testing.
AutoMR:数值变质关系的自动发现和清理
该工件与我们在ICSME 2019上被接受的研究跟踪论文有关[1]。变质关系(MRs)描述了程序输入和输出之间的不变关系。我们提出了一种系统地推断和清洗MRs的新方法AutoMR。AutoMR可以通过一种搜索方法(粒子群优化)发现各种类型的相等和不相等MRs。利用矩阵奇异值分解和约束求解技术去除搜索结果中的冗余MRs。我们在37个数值程序上的实验表明,AutoMR可以有效地推断出准确和简洁的MRs,并且优于最先进的方法。此外,我们还证明了所发现的MRs在突变检测和差分检测中具有较高的故障检测能力。
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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