9.6 Million Links in Source Code Comments: Purpose, Evolution, and Decay
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Abstract (arXiv)
Links are an essential feature of the World Wide Web, and source code repositories are no exception. However, despite their many undisputed benefits, links can suffer from decay, insufficient versioning, and lack of bidirectional traceability. In this paper, we investigate the role of links contained in source code comments from these perspectives. We conducted a large-scale study of around 9.6 million links to establish their prevalence, and we used a mixed-methods approach to identify the links' targets, purposes, decay, and evolutionary aspects. We found that links are prevalent in source code repositories, that licenses, software homepages, and specifications are common types of link targets, and that links are often included to provide metadata or attribution. Links are rarely updated, but many link targets evolve. Almost 10% of the links included in source code comments are dead. We then submitted a batch of link-fixing pull requests to open source software repositories, resulting in most of our fixes being merged successfully. Our findings indicate that links in source code comments can indeed be fragile, and our work opens up avenues for future work to address these problems.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Jan 2019.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.
6 papers.
- 2021DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learningcited by 11
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- 2021FRUGAL: Unlocking SSL for Software Analyticscited by 6
- 2022DebtFree: Minimizing Labeling Cost in Self-Admitted Technical Debt Identification using Semi-Supervised Learningcited by 5
- 2025"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistantscited by 4
- 2026From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentationcited by 0
- 2026From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentation20 Aug 2026
- 2025"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistants17 Aug 2025
- 2024Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study20 Jan 2024
- 2022DebtFree: Minimizing Labeling Cost in Self-Admitted Technical Debt Identification using Semi-Supervised Learning25 Jan 2022
- 2021FRUGAL: Unlocking SSL for Software Analytics22 Aug 2021
- 2021DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning18 Aug 2021