Analysis of SATD in Dockerfiles shows 27% of admissions and 40% of repayments are coupled to non-Dockerfile artifacts, with coupled events repaid faster overall and external dependencies as a key trigger.
Neural network-based detection of self-Admitted technical debt: From performance to explainability.ACM Transactions on Software Engineering and Methodology.2019;28(3)
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A systematic literature review summarizing the shift in SATD detection from heuristic keyword methods to ML, DL, and Transformer models, along with performance trends and open challenges like dataset heterogeneity.
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Beyond the Tip of the Iceberg: Understanding SATD in Dockerfiles through the Lens of Co-evolution
Analysis of SATD in Dockerfiles shows 27% of admissions and 40% of repayments are coupled to non-Dockerfile artifacts, with coupled events repaid faster overall and external dependencies as a key trigger.
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Self-Admitted Technical Debt Detection Approaches: A Decade Systematic Review
A systematic literature review summarizing the shift in SATD detection from heuristic keyword methods to ML, DL, and Transformer models, along with performance trends and open challenges like dataset heterogeneity.