A Review based on Active Research Areas in Mining Software Bug Repositories: Limitations and Possible Future Trends

Fatima Waseem; Farah Haneef; Muhammad Nouman Noor; Aisha Khalid; Hina Rashid; Qudsia Yousaf

Authors

Fatima Waseem Software Engineering Dept. CUST Islamabad, Pakistan
Farah Haneef Software Engineering Dept. CUST Islamabad, Pakistan
Muhammad Nouman Noor AI and Data Science Dept. FAST National University, Pakistan
Aisha Khalid Computer Science Dept. NUML University, Islamabad, Pakistan
Hina Rashid Software Engineering Dept. CUST Islamabad, Pakistan
Qudsia Yousaf Software Engineering Dept. CUST Islamabad, Pakistan

Keywords:

Mining Software Repositories, Bug Localization, Bug Classification, Bug Estimation, Bug Triaging

Abstract

Introduction/ Importance of Study: Bug repository mining is a crucial research area in software engineering, analyzing software change trends, defect prediction, and evolution. It involves developing methods and tools for mining repositories, providing essential data for bug management.

Objective: The goal of this study is to analyze and synthesize recent trends in mining software bug repositories, providing valuable insights for future research and practical bug management.

Novelty statement: Our research contributes novel insights into mining software repository techniques and approaches employed in specific tasks such as bug localization, triaging, and prediction, along with their limitations and possible future trends.

Material and Method: This study presents a comprehensive survey that categorizes and synthesizes the current research within this field. This categorization is derived from an in-depth review of studies conducted over the past fifteen years, from 2010 to 2024. The survey is organized around three key dimensions: the test systems employed in bug repositories, the methodologies commonly used in this area of research, and the prevailing trends shaping the field.

Results and Discussion: Our results highlight the significance of artificial intelligence and machine learning integration in bug repository mining; that has revolutionized software development process by enhancing classification, prediction and vulnerability detection of bugs.

Concluding Remarks: This survey aims to provide a clear and detailed understanding of the evolution of bug repository mining, offering valuable insights for ongoing advancement of software engineering.

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