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首页> 外文期刊>Journal of Software Maintenance and Evolution >Impact analysis in the presence of dependence clusters using Static Execute After in WebKit
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Impact analysis in the presence of dependence clusters using Static Execute After in WebKit

机译：在WebKit中使用Static Execute After在依赖群集存在下进行影响分析

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Impact analysis based on code dependence can provide opportunities to identify parts of the software affected by a change. Because changes usually have far reaching effects in programs, effective and efficient impact analysis is vital. Static Execute After (SEA) is a relation on procedures that is efficiently computable and accurate enough to be a candidate for the use in impact analysis in practice. To assess the applicability of SEA in terms of capturing real defects, we present results on integrating it into the build system of WebKit, a large, open source software system, and on related experiments. We show that a large number of real defects can be captured by impact sets computed by SEA, albeit many of them are large. We demonstrate that this is not an issue in applying it to regression test prioritization, but generally it can be an obstacle in the path to efficient use of impact analysis. We believe that the main reason for large impact sets is the formation of dependence clusters in code. As apparently dependence clusters cannot be easily avoided in the majority of cases, we focus on determining the effects these clusters have on impact analysis and regression test prioritization. Copyright © 2013 John Wiley & Sons, Ltd.
机译：基于代码依赖性的影响分析可以提供机会识别受更改影响的软件部分。由于更改通常会对程序产生深远的影响，因此有效而高效的影响分析至关重要。之后的静态执行（SEA）是与过程的关系，该过程可以有效地计算和精确到足以成为实际影响分析中使用的候选对象。为了评估SEA在捕获实际缺陷方面的适用性，我们提出了将SEA集成到WebKit的构建系统，大型开源软件系统以及相关实验中的结果。我们展示了SEA计算的影响集可以捕获大量实际缺陷，尽管其中许多很大。我们证明这不是将其应用于回归测试优先级的问题，但通常在有效使用影响分析的过程中可能会成为障碍。我们认为产生较大影响集的主要原因是在代码中形成依赖簇。由于在大多数情况下显然无法轻易避免依赖集群，因此我们着重于确定这些集群对影响分析和回归测试优先级的影响。版权所有©2013 John Wiley＆Sons，Ltd.

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