FIXME: Synchronize with Database An Empirical Study of Data Access Self-Admitted Technical Debt
Biruk Asmare Muse, Csaba Nagy, Anthony Cleve, Foutse Khomh, and Giuliano Antoniol

TL;DR
This empirical study investigates self-admitted technical debt in data-intensive systems, analyzing its prevalence, evolution, and composition across numerous open-source projects to inform better debt management strategies.
Contribution
It provides a large-scale analysis of data-access SATD, identifying new categories and revealing insights into their introduction and removal dynamics.
Findings
Most SATDs are introduced later in development cycles.
Bug fixing and refactoring are primary reasons for SATD introduction.
Identified 15 new SATD categories, 11 specific to database access.
Abstract
Developers sometimes choose design and implementation shortcuts due to the pressure from tight release schedules. However, shortcuts introduce technical debt that increases as the software evolves. The debt needs to be repaid as fast as possible to minimize its impact on software development and software quality. Sometimes, technical debt is admitted by developers in comments and commit messages. Such debt is known as self-admitted technical debt (SATD). In data-intensive systems, where data manipulation is a critical functionality, the presence of SATD in the data access logic could seriously harm performance and maintainability. Understanding the composition and distribution of the SATDs across software systems and their evolution could provide insights into managing technical debt efficiently. We present a large-scale empirical study on the prevalence, composition, and evolution of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware Engineering Research · Software System Performance and Reliability · Cloud Computing and Resource Management
