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Change-Aware Dynamic Program Analysis for JavaScript

机译：JavaScript的变更感知动态程序分析

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摘要

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.
机译：动态分析是一种检测正确性，性能和安全问题的强大技术，特别是用于以动态语言编写的程序，例如JavaScript。要尽早捕获错误，开发人员应该定期运行此类分析，例如，通过分析每个提交之前的回归测试套件的执行。遗憾的是，这些分析的高度开销使得这种方法非常昂贵，妨碍开发人员从重量级动态分析的力量受益。本文提出了改变感知动态程序分析，一种方法来制作常用动态分析的方法。关键的想法是识别通过轻量级静态变化影响分析的改变影响的代码的部分，并将对这些受影响部件的动态分析集中在一起。我们基于动态分析框架Jalangi实现了这个想法，并使用DLINT和JITPROF工具的46个跳棋进行评估。我们的结果表明，变更感知动态分析将整体分析时间降低40％，平均减少了所有提交的31％的至少80％。

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