What is it about?
1. Software Quality Assurance 2. Drift in Software Defect Prediction (SDP) 3. Machine Learning in SDP 4. Paired Learning for defect prediction in software defect data 5. Statistical Analysis proofs for comparison 6. Better performance than the available works so far
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Why is it important?
Our findings show that the proposed Pair of Paired Learners Method works as an ensemble of two paired learners and provides better performance of defect prediction when compared to the similar works available so far.
Perspectives
Writing this research paper was a great pleasure as it has co-author with whom I have had long standing collaborations. This article also lead to a greater involvement in software defect prediction research.
Er Arvind Kumar Gangwar
Indian Institute of Technology Roorkee
Read the Original
This page is a summary of: Concept Drift in Software Defect Prediction: A Method for Detecting and Handling the Drift, ACM Transactions on Internet Technology, March 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3589342.
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