On the Diffusion and Impact of Code Smells in Web Applications

Abstract

Web applications (web apps) have become one of the largest parts of the current software market over years. Modern web apps offer several business benefits over other traditional and standalone applications. Mainly, cross-platform compatibility and data integration are some of the critical features that encouraged businesses to shift towards the adoption of Web apps. Web apps are evolving rapidly to acquire new features, correct errors or adapt to new environment changes especially with the volatile context of the web development. These ongoing amends often affect software quality due to poor coding and bad design practices, known as code smells or anti-patterns. The presence of code smells in a software project is widely considered as form of technical debt and makes the software harder to understand, maintain and evolve, besides leading to failures and unforeseen costs. Therefore, it is critical for web apps to monitor the existence and spread of such anti-patterns. In this paper, we specifically target web apps built with PHP being the most used server-side programming language. We conduct the first empirical study to investigate the diffuseness of code smells in Web apps and their relationship with the change proneness of affected code. We detect 12 types of common code smells across a total of 223 releases of 5 popular and long-lived open-source web apps. The key findings of our study include: 1) complex and large classes and methods are frequently committed in PHP files, 2) smelly files are more prone to change than non-smelly files, and 3) Too Many Methods and High Coupling are the most associated smells with files change-proneness.