PHP code smells in web apps: survival and anomalies

TL;DR

This longitudinal study investigates the survival, anomalies, and practitioner attitudes towards PHP code smells in web applications, revealing that scope influences survival time and highlighting the importance of regular refactoring.

Contribution

It provides empirical evidence on code smell survival times, the impact of scope, and introduces anomaly detection to inform better refactoring practices in PHP web apps.

Findings

Localized code smells survive around 4 years

Scattered code smells survive around 5 years

Approximately 60% of code smells are eventually removed

Abstract

Context: Code smells are considered symptoms of poor design, leading to future problems, such as reduced maintainability. Except for anecdotal cases (e. g. code dropout), a code smell survives until it gets explicitly refactored or removed. This paper presents a longitudinal study on the survival of code smells for web apps built with PHP. Objectives: RQ: (i) code smells survival depends on their scope? (ii) practitioners attitudes towards code smells removal in web apps have changed throughout time? (iii) how long code smells survive in web applications? (iv) are there sudden variations (anomalies) in the density of code smells through the evolution of web apps? Method: We analyze the evolution of 6 code smells in 8 web applications written in PHP at the server side, across several years, using the survival analysis technique. We classify code smells according to scope in two categories: scattered and localized. Scattered code smells are expected to be more harmful since their influence is not circumscribed as in localized code smells. We split the observations for each web app into two equal and consecutive timeframes, to test the hypothesis that code smells awareness has increased throughout time. As for the anomalies, we standardize their detection criteria. Results: We present some evidence that code smells survival depends on their scope: the average survival rate decreases in some of them, while the opposite is observed for the remainder. The survival of localized code smells is around 4 years, while the scattered ones live around 5 years. Around 60% of the smells are removed, and some live through all the application life. We also show how a graphical representation of anomalies found in the evolution of code smells allows unveiling the story of a development project and make managers aware of the need for enforcing regular refactoring practices.