This research introduces a novel approach to automatically explain software bugs to developers, addressing a critical gap in the development lifecycle that costs billions annually.

Key Innovations:

• Utilizes Neural Machine Translation to transform code structures into natural language bug explanations
• Focuses on explaining bugs rather than just detecting or fixing them
• Significantly reduces developer time spent understanding bug reports
• Bridges the gap between automated bug detection and human-centered software development

Business Impact: By automating bug explanation, this approach could dramatically reduce the 50% of development time currently spent on debugging activities, lowering costs while improving productivity and code quality.

Explaining Software Bugs Leveraging Code Structures in Neural Machine Translation