基于证据的分析和推断Bug检测的前提条件

D. Brand, M. Buss, V. Sreedhar
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引用次数: 4

摘要

软件维护的一个重要部分是修复软件错误和bug。基于静态分析的工具可以极大地帮助和简化软件维护。为了获得用户的认可,用于检测bug的静态分析工具必须将假警报的发生率降到最低。假警报的一个常见原因是不确定哪些输入被认为是合法的。本文引入循证分析来解决这一问题。基于证据的分析允许人们从输入中推断出合法的先决条件,而无需用户明确指定这些先决条件。我们发现该方法极大地提高了此类静态分析工具的可用性。在本文中,我们报告了我们在工业部署中进行分析的经验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evidence-Based Analysis and Inferring Preconditions for Bug Detection
An important part of software maintenance is fixing software errors and bugs. Static analysis based tools can tremendously help and ease software maintenance. In order to gain user acceptance, a static analysis tool for detecting bugs has to minimize the incidence of false alarms. A common cause of false alarms is the uncertainty over which inputs into a program are considered legal. In this paper we introduce evidence-based analysis to address this problem. Evidence-based analysis allows one to infer legal preconditions over inputs, without having users to explicitly specify those preconditions. We have found that the approach drastically improves the usability of such static analysis tools. In this paper we report our experience with the analysis in an industrial deployment.
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