[2510.08005] Past, Present, and Future of Bug Tracking in the Generative AI Era

Computer Science > Software Engineering arXiv:2510.08005 (cs) [Submitted on 9 Oct 2025 (v1), last revised 30 Mar 2026 (this version, v3)] Title:Past, Present, and Future of Bug Tracking in the Generative AI Era Authors:Utku Boran Torun, Mehmet Taha Demircan, Mahmut Furkan Gön, Eray Tüzün View a PDF of the paper titled Past, Present, and Future of Bug Tracking in the Generative AI Era, by Utku Boran Torun and 3 other authors View PDF HTML (experimental) Abstract:Traditional bug-tracking systems rely heavily on manual reporting, reproduction, classification, and resolution, involving multiple stakeholders such as end users, customer support, developers, and testers. This division of responsibilities requires substantial coordination and human effort, widens the communication gap between non-technical users and developers, and significantly slows the process from bug discovery to deployment. Moreover, current solutions are highly asynchronous, often leaving users waiting long periods before receiving any feedback. In this paper, we examine the evolution of bug-tracking practices, from early paper-based methods to today's web-based platforms, and present a forward-looking vision of an AI-powered bug tracking framework. The framework augments existing systems with large language model (LLM) and agent-driven automation, and we report early adaptations of its key components, providing initial empirical grounding for its feasibility. The proposed framework aims to reduce time to r...