Presenter: Thodoris Sotiropoulos
Date: 12 November 2018

Asynchrony has become an inherent element of JavaScript because it is a mean for improving the scalability and performance of modern web applications. To this end, JavaScript provides programmers with a wide range of constructs and features for developing code that performs asynchronous computations, including but not limited to timers, promises and non-blocking I/O. However, the data flow imposed by asynchrony is implicit and is not always well-understood by the developers who introduce many asynchrony-related bugs to their programs. Even worse, there are few tools and techniques available for analysing and reasoning about such asynchronous applications. In this work, we address this issue by designing and implementing one of the first static analysis schemes capable of dealing with almost all the asynchronous primitives of JavaScript up to the 7th edition of the ECMAScript specification. Specifically, we introduce callback graph, a representation for capturing data flow between asynchronous code. We exploit the callback graph for designing a more precise analysis that respects the execution order between different asynchronous functions. We parameterise our analysis with two novel context-sensitivity strategies and we end up with multiple analysis variations for building callback graph. Then we perform a number of experiments on a set of hand-written and real-world JavaScript programs. Our results show that our analysis can be applied to medium-sized programs achieving 79% precision. The findings further suggest that analysis sensitivity is able to improve accuracy up to 11,3% on average, without highly sacrificing performance.