演化软件系统的快速分析

Anushri Jana, Bharti Chimdyalwar, Susheel Kumar, R. Venkatesh
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引用次数: 0

摘要

在本文中,我们提出了一种算法,可以有效地更新数据流分析结果,以响应增量变化。我们的增量算法分两个阶段工作:在阶段1中,它通过以自下而上的顺序遍历调用图来计算所选过程的摘要;在阶段2中,它通过以自上而下的顺序遍历调用图来更新所选过程的数据流值,从而使分析更快。程序的选择是通过比较不同版本的摘要来完成的。我们已经在我们专有的静态分析工具中实现了这个算法,多年来被许多客户用于自动缺陷检测。对我们的算法在核心银行应用程序上的评估表明,与详尽的分析相比,它平均花费的时间减少了90%,这证明了我们的算法在现实世界不断发展的软件系统上的实际优势。
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Fast Analysis of Evolving Software Systems
In this paper, we present an algorithm that efficiently updates results of dataflow analysis in response to incremental changes. Our incremental algorithm work in two phases: it compute summaries for selected procedures in phase 1 by traversing the call graph in bottom-up order and, in phase 2, it updates the dataflow values for selected procedures by traversing call graph in top-down order, thus making the analysis faster. The selection of procedures is done by comparing summaries across the version. We have implemented this algorithm in our proprietary static analysis tool, used by many clientele over the years, for automated defect detection. An evaluation of our algorithm on a core banking application shows that on an average it takes 90 % lesser time in comparison to an exhaustive analysis, demonstrating practical benefit of our algorithm on a real-world evolving software system.
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