Work

DrAsync: identifying and visualizing anti-patterns in asynchronous JavaScript

Year: 2022

Type: conference-paper

Abstract: Promises and async/await have become popular mechanisms for implementing asynchronous computations in JavaScript, but despite their popularity, programmers have difficulty using them. This paper identifies 8 anti-patterns in promise-based JavaScript code that are prevalent across popular JavaScript repositories. We present a light-weight static analysis for automatically detecting these anti-patterns. This analysis is embedded in an interactive visualization tool that additionally relies on dynamic analysis to visualize promise lifetimes and instances of anti-patterns executed at run time. By enabling the user to navigate between promises in the visualization and the source code fragments that they originate from, problems and optimization opportunities can be identified.

Source: ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

DOI: 10.1145/3510003.3510097

Authors: Alexi Turcotte, Michael D. Shah, Mark W. Aldrich, Frank Tip

Institutions: Northeastern University, Tufts University

Language: English

Topic: Software Engineering Research

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Natural Sciences and Engineering Research Council of Canada

Awards: G224146728, SHF: Small: Testing and Profiling Asynchronous Software