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引用次数: 2

摘要

JavaScript是最流行的编程语言之一。然而,理解JavaScript应用程序的动态行为在实践中是具有挑战性的。有很多因素会阻碍JavaScript的理解,比如它的动态、异步和事件驱动的特性,JavaScript和文档对象模型之间的动态交互,以及客户端和服务器之间的异步通信。在这项研究工作中,我们已经提出了理解基于事件和异步JavaScript行为的方法。为了增强我们方法的可扩展性,我们提出了一种采用生物信息学算法的新技术,从形成高级模式的执行痕迹中提取动作序列。
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Understanding behavioural patterns in JavaScript
JavaScript is one of the most popular programming languages. How- ever, understanding the dynamic behaviour of JavaScript apps is challenging in practice. There are many factors that hinder JavaScript comprehension, such as its dynamic, asynchronous, and event- driven nature, the dynamic interplay between JavaScript and the Document Object Model, and the asynchronous communication between client and server. In this research work, we have already proposed methods for understanding event-based and asynchronous JavaScript behaviour. To enhance the scalability of our methods, we propose a new technique that adopts bio-informatics algorithms to extract sequences of actions from execution traces that form higher-level patterns.
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