Incorporating additional types of auxiliary information can further enhance the function-level APR techniques. Some potential types of auxiliary information that can be considered include:
Version Control Data: Analyzing version control data such as commit messages, code diffs, and code review comments can provide valuable insights into the evolution of the codebase and the context of the bug.
Execution Traces: Utilizing execution traces from debugging sessions or runtime monitoring can help in understanding the runtime behavior of the program and identifying potential bug triggers.
Code Metrics: Leveraging code metrics such as cyclomatic complexity, code churn, and code smells can provide additional context on the quality and complexity of the code, aiding in bug localization and repair.
Domain-specific Knowledge: Incorporating domain-specific knowledge related to the application or industry can help in understanding the specific requirements and constraints of the software, leading to more targeted and effective bug fixes.
User Feedback: Integrating user feedback, bug reports, and feature requests can provide valuable insights into user expectations and issues, guiding the repair process towards addressing user concerns.
By incorporating these additional types of auxiliary information, function-level APR techniques can gain a more comprehensive understanding of the codebase and the bugs, leading to more accurate and effective bug fixes.