Static analysis of JavaScript libraries in a scalable and precise way using loop sensitivity

Abstract

Statically analyzing JavaScript applications often requires an analysis of JavaScript libraries because many JavaScript applications use libraries. However, static analysis techniques for JavaScript are not yet ready for analyzing libraries in a scalable and precise manner. Simply loading JavaScript libraries uses various dynamic features of JavaScript, which cause static analyzers to suffer from mutually intermingled problems of scalability and imprecision. In this paper, we present a loop-sensitive analysis (LSA) technique, which can improve the analysis scalability when analyzing JavaScript libraries by enhancing the analysis precision of loops. The LSA technique distinguishes loop iterations when loop conditions can be determined to be either true or false precisely. We formalize LSA in the abstract interpretation framework in the presence of tricky language features such as exceptions and prove its soundness and precision theorems using Coq. We evaluate our LSA implementation with the analysis results of programs that use 5 JavaScript libraries and show that LSA significantly improves the analysis scalability and precision of an existing JavaScript static analyzer when analyzing JavaScript libraries. In addition, using the configurability of LSA, we experimentally show the correlation between scalability and precision in the analysis of JavaScript libraries. We found that even the analysis of simple programs that just load jQuery, which is the most popular JavaScript library, in a scalable way requires distinguishing not only the last 4 functions being called but also 40 iterations in each loop with 2-level nested loops at least. Both the mechanization and implementation of LSA are publicly available.