A large-scale empirical study of code smells in JavaScript projects

Abstract

JavaScript is a powerful scripting programming language that has gained a lot of attention this past decade. Initially used exclusively for client-side web development, it has evolved to become one of the most popular programming languages, with developers now using it for both client-side and server-side application development. Similar to applications written in other programming languages, JavaScript applications contain code smells, which are poor design choices that can negatively impact the quality of an application. In this paper, we perform a large-scale study of JavaScript code smells in server-side and client-side applications, with the aim to understand how they impact the fault-proneness of applications, and how they are evolved by the developers of the applications. We detect 12 types of code smells in 1807 releases of 15 popular JavaScript applications (i.e., express, grunt, bower, less.js, request, jquery, vue, ramda, leaflet, hexo, chart, webpack, webtorrent, moment, and riot) and perform survival analysis, comparing the time until a fault occurrence, in files containing code smells and files without code smells. We also examine the introduction and removal of the code smells in the applications using survival models. All our analysis are conducted at the granularity of the line of code. Results show that (1) on average, files without code smells have hazard rates at least 33% lower than files with code smells. (2) Among the studied smells, “Variable Re-assign,” “Assignment In Conditional statements,” and “Complex Code” smells have the highest fault hazard rates. (3) Code smells, and particularly “Variable Re-assign,” are often introduced in the application when the files containing them are created. Moreover, they tend to remain in the applications for a long period of time; “Variable Re-assign” is also the most prevalent code smell. Overall, code smells affect negatively the quality of JavaScript applications and developers should consider tracking and removing them early on before the release of applications to the public.