3 papers
cs.LG2026
Training Dynamics of Neural Software Defect Predictors under Coupled Data-Quality Issues
Emmanuel Charleson Dapaah, Philip Makedonski, Jens Grabowski
Context: Software defect prediction supports maintenance decisions such as testing prioritization, release-risk assessment, and quality monitoring. However, metric-based SDP datase…
cs.SE2026
Quality-Driven Selective Mutation for Deep Learning
Zaheed Ahmed, Emmanuel Charleson Dapaah, Philip Makedonski +1
Mutants support testing and debugging in two roles: (i) as test goals and (ii) as substitutes for real faults. Hard-to-kill mutants provide better guidance for test improvement, wh…
cs.SE2025
When Data Quality Issues Collide: A Large-Scale Empirical Study of Co-Occurring Data Quality Issues in Software Defect Prediction
Emmanuel Charleson Dapaah, Jens Grabowski
Software Defect Prediction (SDP) models are central to proactive software quality assurance, yet their effectiveness is often constrained by the quality of available datasets. Prio…