Visually Exploring Software Maintenance Activities
This work provides incremental tools for software practitioners to monitor and maintain project health by identifying anomalies in maintenance activities.
The authors tackled the problem of understanding software maintenance activities by proposing visualizations for exploring corrective, perfective, and adaptive tasks in both project and developer scopes, resulting in a prototype built with the Shiny R framework and an online demo for analyzing open-source projects.
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.