Computer Science Events
PhD Defense- Yang Song, Computer Science
Abstract:
Software development is a critical process in various domains, but it often encounters challenges due to the complexity of software systems. One challenge is bug report management, which is a critical yet challenging process that affects the efficiency of the software development process. This process involves several key steps from reporting to resolution. It begins with reporting bugs, followed by triage to evaluate their priority and severity, detection of duplicates, and assignment to the appropriate developers. The resolution phase includes bug localization, design changes, and implementation such as code refactoring. This process ends with a thorough verification involving code review and testing.
However, the current bug management process faces significant challenges due to the overwhelming volume and variety of bug reports, making tasks such as reporting, assignment, localization, and fixing increasingly complex. These challenges highlight a need for innovative approaches aimed at enhancing the overall bug management process, thereby improving the effectiveness of software development.
This dissertation explores the potential of automating the bug management process to optimize the effectiveness of software development and maintenance. It focuses on three crucial stages in the bug management process: bug reporting, bug assignment, and bug localization. This dissertation will present four innovative works designed to enhance these phases. The initial two works focus on bug reporting, the third on bug assignment, and the fourth on bug localization.
First, the dissertation discusses the challenges faced by developers due to poor-quality bug reports on GitHub, often lacking crucial details. This leads to excessive effort in bug fixing and issues with reproducing bugs. To address this, the dissertation leverages machine learning to automatically analyze user-written bug reports, identifying key elements of the software system. It aims to automate bug report analysis and inform reporters to provide the missing information timely, thereby enhancing the quality of bug reports and aiding developers in bug triage and resolution.
Second, the dissertation proposes an interactive bug reporting system for end-users, implemented as a task-oriented chatbot named Burt. This system guides users through the bug reporting process, offering real-time feedback on each element of a bug description and interactive suggestions to bridge the knowledge gap between end-users and developers. It is designed to make bug reporting more engaging and user-friendly while ensuring the generation of high-quality, informative reports.
Third, the dissertation investigates the efficacy of automated methods for recommending developers for bug reports in open-source software projects. It reveals that these methods do not perform consistently across different reports, leading to a proposal for using the most effective method for each report, assessed through machine learning. The findings suggest a gap in the understanding of real-world bug assignment processes and call for further research in this area.
Lastly, the dissertation explores different deep learning models that can automatically localize buggy UI screens and components from the bug descriptions of mobile apps. This approach is critical for understanding, diagnosing, and resolving underlying bugs in GUI-centric software applications.
Together, these contributions present a comprehensive strategy for enhancing the automated bug report management process, promising significant improvements to the efficiency and effectiveness of the software development process.
Bio:
Yang Song is a Ph.D. Candidate in the Department of Computer Science at William & Mary. Her Ph.D. advisor is Prof. Oscar Chaparro. Her research interests mainly include software maintenance and evolution, bug reporting, bug triage and resolution, and machine learning. Her Ph.D. research works have been accepted by FSE2020, 2022, and ICSE 2023. Previously, she received her Bachelor of Mathematics at Sichuan University, China in 2016.
Sponsored by: Computer Science