IDEAL: An Open-Source Identifier Name Appraisal Tool
This addresses the issue of code comprehension for software developers, but it is incremental as it builds on existing anti-pattern detection methods.
The paper tackles the problem of poor identifier naming in code by presenting IDEAL, an open-source tool that provides feedback on naming practices, including linguistic anti-pattern detection, to improve code legibility for developers.
Developers must comprehend the code they will maintain, meaning that the code must be legible and reasonably self-descriptive. Unfortunately, there is still a lack of research and tooling that supports developers in understanding their naming practices; whether the names they choose make sense, whether they are consistent, and whether they convey the information required of them. In this paper, we present IDEAL, a tool that will provide feedback to developers about their identifier naming practices. Among its planned features, it will support linguistic anti-pattern detection, which is what will be discussed in this paper. IDEAL is designed to, and will, be extended to cover further anti-patterns, naming structures, and practices in the near future. IDEAL is open-source and publicly available, with a demo video available at: https://youtu.be/fVoOYGe50zg