Physical Sciences and Mathematics Commons^™

Fuzzy And Probabilistic Rule-Based Approaches To Identify Fault Prone Files, Piyush Kumar Korlepara

Electronic Thesis and Dissertation Repository

Most software fault proneness prediction techniques utilize machine learning models which act as black boxes when performing predictions. Software developers cannot obtain any insights as to why such trained models reached their conclusions when applied to new data. This leads to a reduced confidence in accepting the prediction results while applying the model in complex systems. In this thesis, we propose two rule-based and programming language-agnostic fault proneness prediction techniques. The first technique utilizes fuzzy reasoning, while the second utilizes Markov Logic Networks. The rules operate on facts that are produced by harvesting and postprocessing raw data extracted from the …