JavaScript的变化感知动态程序分析

Dileep Ramachandrarao Krishna Murthy, Michael Pradel
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引用次数: 2

摘要

动态分析是一种检测正确性、性能和安全性问题的强大技术,特别是对于用动态语言(如JavaScript)编写的程序。为了尽早发现错误,开发人员应该定期运行这样的分析,例如,在每次提交之前分析回归测试套件的执行情况。不幸的是,这些分析的高开销使得这种方法非常昂贵,阻碍了开发人员从重量级动态分析的强大功能中获益。本文提出了变化感知动态程序分析,这是一种使一类常见的动态分析实现变化感知的方法。关键思想是通过轻量级的静态更改影响分析来识别受更改影响的代码部分,并将动态分析的重点放在这些受影响的部分上。我们基于动态分析框架Jalangi实现了这个想法,并使用来自DLint和JITProf工具的46个检查器对其进行了评估。我们的结果表明,变化感知动态分析平均减少了40%的总体分析时间,并且在31%的提交中至少减少了80%的分析时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Change-Aware Dynamic Program Analysis for JavaScript
Dynamic analysis is a powerful technique to detect correctness, performance, and security problems, in particular for programs written in dynamic languages, such as JavaScript. To catch mistakes as early as possible, developers should run such analyses regularly, e.g., by analyzing the execution of a regression test suite before each commit. Unfortunately, the high overhead of these analyses make this approach prohibitively expensive, hindering developers from benefiting from the power of heavyweight dynamic analysis. This paper presents change-aware dynamic program analysis, an approach to make a common class of dynamic analyses change-aware. The key idea is to identify parts of the code affected by a change through a lightweight static change impact analysis, and to focus the dynamic analysis on these affected parts. We implement the idea based on the dynamic analysis framework Jalangi and evaluate it with 46 checkers from the DLint and JITProf tools. Our results show that change-aware dynamic analysis reduces the overall analysis time by 40%, on average, and by at least 80% for 31% of all commits.
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