A Critical Comparison on Six Static Analysis Tools: Detection, Agreement, and Precision

TL;DR

This study compares six popular static analysis tools for Java, revealing their limited agreement and low precision, and provides a comprehensive taxonomy of their warnings to inform better tool selection and development.

Contribution

It offers the first large-scale comparison of six Java static analysis tools, analyzing their warning taxonomy, agreement, and precision.

Findings

Little to no agreement among tools

Low precision of static analysis warnings

Comprehensive taxonomy of tool warnings

Abstract

Background. Developers use Automated Static Analysis Tools (ASATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder for practitioners to select the most suitable one for their needs. To better support developers, researchers have been conducting several studies on ASATs to favor the understanding of their actual capabilities. Aims. Despite the work done so far, there is still a lack of knowledge regarding (1) which source quality problems can actually be detected by static analysis tool warnings, (2) what is their agreement, and (3) what is the precision of their recommendations. We aim at bridging this gap by proposing a large-scale comparison of six popular static analysis tools for Java projects: Better Code Hub, CheckStyle, Coverity Scan, Findbugs, PMD, and SonarQube. Method. We analyze 47 Java projects and derive a taxonomy of warnings raised by 6 state-of-the-practice ASATs. To assess their agreement, we compared them by manually analyzing - at line-level - whether they identify the same issues. Finally, we manually evaluate the precision of the tools. Results. The key results report a comprehensive taxonomy of ASATs warnings, show little to no agreement among the tools and a low degree of precision. Conclusions. We provide a taxonomy that can be useful to researchers, practitioners, and tool vendors to map the current capabilities of the tools. Furthermore, our study provides the first overview on the agreement among different tools as well as an extensive analysis of their precision.