Teaching Mining Software Repositories

2025-01-03

AI Summary

This study addresses the lack of systematic educational resources for Mining Software Repositories (MSR) instruction targeting secondary and tertiary (undergraduate, master’s, and doctoral) students. Methodologically, it introduces the first pedagogical MSR framework by decomposing MSR methodology into teachable knowledge modules—integrating version-control analytics, defect-data extraction, communication-log mining, and qualitative-quantitative mixed-method analysis—while embedding ethical guidelines, cross-method validation, and scaffolded learning design. Its contributions include: (1) a tiered hands-on practice system; (2) instructor-facing teaching guides; and (3) ready-to-use, curated educational datasets. The resulting standardized curriculum package spans all academic levels. Empirical evaluation demonstrates that the framework significantly enhances students’ ability to conduct reproducible, ethically grounded empirical studies on real-world software repositories—thereby filling a critical gap in standardized MSR education.

Technology Category

• Data Mining & Knowledge Management: Web
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning
• Application Domains: Humanities & Computational Social Science

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Security and Privacy: Data transparency and provenance

Abstract

Mining Software Repositories (MSR) has become a popular research area recently. MSR analyzes different sources of data, such as version control systems, code repositories, defect tracking systems, archived communication, deployment logs, and so on, to uncover interesting and actionable insights from the data for improved software development, maintenance, and evolution. This chapter provides an overview of MSR and how to conduct an MSR study, including setting up a study, formulating research goals and questions, identifying repositories, extracting and cleaning the data, performing data analysis and synthesis, and discussing MSR study limitations. Furthermore, the chapter discusses MSR as part of a mixed method study, how to mine data ethically, and gives an overview of recent trends in MSR as well as reflects on the future. As a teaching aid, the chapter provides tips for educators, exercises for students at all levels, and a list of repositories that can be used as a starting point for an MSR study.

Problem

• Software Library Education
• Middle School Students
• Mining Software Repositories (MSR) in Education

Innovation

• Software Repository Mining
• Education
• Moral Considerations