The Dual-Edged Sword of Technical Debt: Benefits and Issues Analyzed Through Developer Discussions
Xiaozhou Li, Matteo Esposito, Andrea Janes, Valentina, Lenarduzzi

TL;DR
This study systematically analyzes practitioners' opinions on technical debt through NLP techniques applied to a large collection of forum posts, revealing key topics, sentiments, and challenges in managing technical debt.
Contribution
It introduces a comprehensive NLP-based approach to understanding developer perspectives on technical debt from large-scale online discussions, highlighting key themes and sentiments.
Findings
Eight main topics of technical debt identified
Practitioners' positive and negative opinions mapped
Challenges include unclear roles and engagement issues
Abstract
Background. Technical debt (TD) has long been one of the key factors influencing the maintainability of software products. It represents technical compromises that sacrifice long-term software quality for potential short-term benefits. Objective. This work is to collectively investigate the practitioners' opinions on the various perspectives of TD from a large collection of articles. We find the topics and latent details of each, where the sentiments of the detected opinions are also considered. Method. For such a purpose, we conducted a grey literature review on the articles systematically collected from three mainstream technology forums. Furthermore, we adopted natural language processing techniques like topic modeling and sentiment analysis to achieve a systematic and comprehensive understanding. However, we adopted ChatGPT to support the topic interpretation. Results. In this…
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Taxonomy
TopicsEconomic Theory and Policy · Economic Growth and Productivity
