Uddin, GiasTamanna, Salma Begum2024-06-072024-06-072024-06-04Tamanna, S. B. (2024). AI-assisted interactive assistants for software issue report understanding (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.https://hdl.handle.net/1880/118910https://doi.org/10.11575/PRISM/46507Issue reports in software projects often become complex due to their technical details and lengthy discussions, leading to information overload. This complexity can hinder quick understanding of these reports, impacting the development process adversely. This thesis investigates whether automatic assistance can help tackle the problem. It first introduces the iSum (issue summarizer) tool, designed to generate visual summaries of information types present in issue reports and analyze the prevalence and trends of these across a report or a repository. Next, it addresses a RAG-based ChatGPT’s struggle with understanding complex technical content from bug reports and interpreting context from queries for exploring bug reports. Our enhancement, the ChatGPT Inaccuracy Mitigation Engine (CHIME), boosts response correctness of ChatGPT by around 30%. Both iSum and CHIME demonstrate the potential of AI to enhance the comprehensibility of issue reports, taking a step forward in efficient issue understanding.enUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Engineering--Electronics and Electricalmaster thesis