A Longitudinal Study of Static Analysis Warning Evolution and the Effects of PMD on Software Quality in Apache Open Source Projects

TL;DR

This longitudinal study investigates how static analysis warnings evolve in open source projects, focusing on PMD's impact on code quality and warning trends over 17 years.

Contribution

It provides the first empirical analysis of PMD warning trends in open source projects, revealing the effects of coding style changes and PMD's role in software quality.

Findings

Large global warning changes are mainly due to style adjustments.

PMD's presence in build process has minimal impact on warning removal.

PMD presence correlates with improved defect density.

Abstract

Automated static analysis tools (ASATs) have become a major part of the software development workflow. Acting on the generated warnings, i.e., changing the code indicated in the warning, should be part of, at latest, the code review phase. Despite this being a best practice in software development, there is still a lack of empirical research regarding the usage of ASATs in the wild. In this work, we want to study ASAT warning trends in software via the example of PMD as an ASAT and its usage in open source projects. We analyzed the commit history of 54 projects (with 112,266 commits in total), taking into account 193 PMD rules and 61 PMD releases. We investigate trends of ASAT warnings over up to 17 years for the selected study subjects regarding changes of warning types, short and long term impact of ASAT use, and changes in warning severities. We found that large global changes in ASAT warnings are mostly due to coding style changes regarding braces and naming conventions. We also found that, surprisingly, the influence of the presence of PMD in the build process of the project on warning removal trends for the number of warnings per lines of code is small and not statistically significant. Regardless, if we consider defect density as a proxy for external quality, we see a positive effect if PMD is present in the build configuration of our study subjects.