Visually Exploring Software Maintenance Activities

TL;DR

This paper presents visualizations for analyzing software maintenance activities, helping practitioners monitor project health and identify anomalies in maintenance patterns across projects and developers.

Contribution

It introduces a visualization approach and a prototype tool for exploring and understanding software maintenance activities at project and individual levels.

Findings

Visualizations reveal maintenance activity patterns and imbalances.

The prototype enables exploration of open source project data.

Tools assist in detecting anomalies in maintenance activities.

Abstract

Lehman's Laws teach us that a software system will become progressively less satisfying to its users over time, unless it is continually adapted to meet new needs. A line of previous works sought to better understand software maintenance by studying how commits can be classified into three main software maintenance activities. Corrective: fault fixing; Perfective: system improvements; Adaptive: new feature introduction. In this work we suggest visualizations for exploring software maintenance activities in both project and individual developer scopes. We demonstrate our approach using a prototype we have built using the Shiny R framework. In addition, we have also published our prototype as an online demo. This demo allows users to explore the maintenance activities of a number of popular open source projects. We believe that the visualizations we provide can assist practitioners in monitoring and maintaining the health of software projects. In particular, they can be useful for identifying general imbalances, peaks, deeps and other anomalies in projects' and developers' maintenance activities.