Digging into Semantics: Where Do Search-Based Software Repair Methods Search?
Digging into Semantics: Where Do Search-Based Software Repair Methods Search?
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DOI：
10.1007/978-3-031-14721-0_1
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Hammad Ahmad;Padriac Cashin;S. Forrest;Westley Weimer
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文献类型：
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作者：
Hammad Ahmad;Padriac Cashin;S. Forrest;Westley Weimer
基于搜索的方法是自动修复软件错误的一种流行方法，这一领域称为自动程序修复（APR）。有越来越多的兴趣，在经验评估和比较不同的APR方法，通常衡量为基准集的故障程序的成功修复率。然而，这样的评估无法解释为什么有些方法成功，而另一些方法失败。因为这些方法通常使用语法表示，即，源代码中，我们对不同方法如何探索其语义空间知之甚少，这与评估修复质量和理解搜索动态有关。我们提出了一种基于程序语义的自动化方法，该方法提供了有关不同APR搜索技术的定量和定性信息。我们的方法不需要手动注释，并产生数学和人类可理解的见解。在对4种APR工具和34种缺陷的实证评估中，我们调查了搜索空间探索、语义多样性和修复成功之间的关系，考察了整体情况以及工具的搜索如何展开。我们的研究结果表明，仅凭种群多样性不足以找到修复方法，在正确的地方搜索比广泛搜索更重要，这为研究界指明了未来的方向。
Search-based methods are a popular approach for automatically repairing software bugs, a field known as automated program repair (APR). There is increasing interest in empirical evaluation and comparison of different APR methods, typically measured as the rate of successful repairs on benchmark sets of buggy programs. Such evaluations, however, fail to explainwhysome approaches succeed and others fail. Because these methods typically use syntactic representations, i.e., source code, we know little about how the different methods explore their semantic spaces, which is relevant for assessing repair quality and understanding search dynamics. We propose an automated method based on program semantics, which provides quantitative and qualitative information about different APR search-based techniques. Our approach requires no manual annotation and produces both mathematical and human-understandable insights. In an empirical evaluation of 4 APR tools and 34 defects, we investigate the relationship between search-space exploration, semantic diversity and repair success, examining both the overall picture and how the tools’ search unfolds. Our results suggest that population diversity alone is not sufficient for finding repairs, and that searching in the right place is more important than searching broadly, highlighting future directions for the research community.