AI‑Powered Debugging with IBM Bob

Debugging is one of the most time‑consuming and frustrating tasks in software development. Developers often spend hours scanning logs, reproducing errors, and manually fixing issues. This slows down productivity, delays delivery, and increases the risk of mistakes. Our hackathon project demonstrates how IBM Bob DebuggingAgent can transform this workflow by automating error analysis and providing actionable fixes in real time. We built a deliberately buggy Node.js application containing ten different errors across runtime, syntax, asynchronous logic, file handling, and middleware. Each bug was designed to represent common challenges developers face in everyday coding. Examples include undefined variables, invalid JSON parsing, missing asynchronous functions, division by zero, incorrect property access, file system errors, unhandled promise rejections, type mismatches, invalid array operations, and middleware misconfiguration. By running the app and visiting specific routes, each bug produces error logs that are captured in the terminal. Instead of manually debugging these issues, we fed the error logs directly into IBM Bob IDE using the DebuggingAgent. Bob automatically categorized the errors, explained the root causes, suggested fixes with code snippets, and even generated commit messages and pull requests. This workflow demonstrates how AI can act as a real debugging assistant, reducing the need for repetitive manual effort. For example, when the /users route crashed due to an undefined variable, Bob identified the runtime error, explained that users was undefined, and suggested initializing the variable or adding a conditional check. Similarly, for the /data route, Bob highlighted the invalid JSON format and proposed correcting the string to valid JSON syntax. To provide evidence of Bob’s capabilities, we captured screenshots of each debugging session and stored them in the bob_sessions folder. These screenshots show the full cycle: error logs, Bob’s analysis, suggested fixes, and generated commits. This visual proof strengthens the project by demonstrating real AI‑assisted debugging in action. The impact of this approach is significant. Manual debugging of each bug typically takes 10–15 minutes, depending on complexity. With Bob, the same process is reduced to 3–5 minutes. Across multiple bugs, this represents a time savings of nearly 70%. More importantly, Bob ensures consistency in error handling and reduces the likelihood of human oversight. Developers can focus on building features while Bob handles repetitive debugging tasks. Our project structure is simple and clear: the original exercises remain in the base repo, while our solution is contained in the my_solution folder with the buggy app, documentation, and README. The bob_sessions folder holds screenshots of Bob’s debugging sessions. Together, these elements provide a complete demonstration of how AI can accelerate debugging workflows. In conclusion, this project showcases the practical benefits of integrating IBM Bob into real development environments. By automating error detection and resolution, Bob empowers developers to debug smarter, not harder, ultimately improving productivity and software quality.