4 citations · 4 across the 3 of their papers we have counts for
6 papers · 1 filter
Reducing Labeling Effort in Architecture Technical Debt Detection through Active Learning and Explainable AI
Edi Sutoyo, Paris Avgeriou, Andrea Capiluppi
Self-Admitted Technical Debt (SATD) refers to technical compromises explicitly admitted by developers in natural language artifacts, such as code comments, commit messages, and iss…
The Dangers of Non-Self-Fixed Architecture Technical Debt and Its Impact on Time-to-Fix
Edi Sutoyo, Paris Avgeriou, Andrea Capiluppi
Technical Debt (TD) refers to the long-term costs incurred when developers prioritize short-term delivery over quality-improving work. Architectural Technical Debt (ATD) arises whe…
Self-Admitted Technical Debt Detection Approaches: A Decade Systematic Review
Edi Sutoyo, Andrea Capiluppi
Technical debt (TD) refers to the long-term costs associated with suboptimal design or code decisions in software development, often made to meet short-term delivery goals. Self-Ad…
Tracing the Lifecycle of Architecture Technical Debt in Software Systems: A Dependency Approach
Edi Sutoyo, Paris Avgeriou, Andrea Capiluppi
Architectural technical debt (ATD) represents trade-offs in software architecture that accelerate initial development but create long-term maintenance challenges. ATD, in particula…
Development and Adoption of SATD Detection Tools: A State-of-practice Report
Edi Sutoyo, Andrea Capiluppi
Self-Admitted Technical Debt (SATD) refers to instances where developers knowingly introduce suboptimal solutions into code and document them, often through textual artifacts. This…
Deep Learning and Data Augmentation for Detecting Self-Admitted Technical Debt
Edi Sutoyo, Paris Avgeriou, Andrea Capiluppi
Self-Admitted Technical Debt (SATD) refers to circumstances where developers use textual artifacts to explain why the existing implementation is not optimal. Past research in detec…