English

Source Code Hotspots: A Diagnostic Method for Quality Issues

Software Engineering 2026-02-16 v1

Abstract

Software source code often harbours "hotspots": small portions of the code that change far more often than the rest of the project and thus concentrate maintenance activity. We mine the complete version histories of 91 evolving, actively developed GitHub repositories and identify 15 recurring line-level hotspot patterns that explain why these hotspots emerge. The three most prevalent patterns are Pinned Version Bump (26%), revealing brittle release practices; Long Line Change (17%), signalling deficient layout; and Formatting Ping-Pong (9%), indicating missing or inconsistent style automation. Surprisingly, automated accounts generate 74% of all hotspot edits, suggesting that bot activity is a dominant but largely avoidable source of noise in change histories. By mapping each pattern to concrete refactoring guidelines and continuous integration checks, our taxonomy equips practitioners with actionable steps to curb hotspots and systematically improve software quality in terms of configurability, stability, and changeability.

Keywords

Cite

@article{arxiv.2602.13170,
  title  = {Source Code Hotspots: A Diagnostic Method for Quality Issues},
  author = {Saleha Muzammil and Mughees Ur Rehman and Zoe Kotti and Diomidis Spinellis},
  journal= {arXiv preprint arXiv:2602.13170},
  year   = {2026}
}

Comments

Published at the 23rd International Conference on Mining Software Repositories

R2 v1 2026-07-01T10:35:43.289Z