3 papers
cs.SE2025
Detection, Classification and Prevalence of Self-Admitted Aging Debt
Murali Sridharan, Mika Mäntylä, Leevi Rantala
Context: Previous research on software aging is limited with focus on dynamic runtime indicators like memory and performance, often neglecting evolutionary indicators like source c…
cs.SE2023
PENTACET data -- 23 Million Contextual Code Comments and 250,000 SATD comments
Murali Sridharan, Leevi Rantala, Mika Mäntylä
Most Self-Admitted Technical Debt (SATD) research utilizes explicit SATD features such as 'TODO' and 'FIXME' for SATD detection. A closer look reveals several SATD research uses si…
cs.SE2021
Data Balancing Improves Self-Admitted Technical Debt Detection
Murali Sridharan, Mika Mantyla, Leevi Rantala +1
A high imbalance exists between technical debt and non-technical debt source code comments. Such imbalance affects Self-Admitted Technical Debt (SATD) detection performance, and ex…