Generative AI for Automated Software Debugging and Repair
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Solution Overview
Problem
Existing software debugging solutions require manual investigation and repair of reliability issues in operating systems and applications, which is time-consuming and prone to human error.
Innovation Solution
A generative artificial intelligence system is used to automatically detect and repair reliability issues by analyzing error information, building an error context, and providing input to a language model to explain the intent of software code, identify the cause of failures, and propose solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual debugging process is used, then developers can understand and repair source code, but the process is time-consuming and prone to human error
Solution Approach 1:
The system enables self-service debugging by allowing the AI model to automatically analyze error information, identify problematic code, and generate repair solutions without requiring manual developer intervention for each step of the debugging process
Solution Approach 2:
The patent replaces the mechanical manual debugging process with an automated AI-based system that uses natural language processing and code analysis to detect and repair reliability issues, substituting human manual effort with intelligent automation
2Ease of operation
If manual investigation of source code is required, then developers can identify error causes, but the process requires high technical aptitude and is complex
Solution Approach 1:
The AI model acts as an intermediary between the error information and the developer, automatically analyzing the complex source code and error contexts to identify problems and generate repair solutions, thereby simplifying the interaction for developers
Solution Approach 2:
The system extracts and isolates the specific problematic code sections and error information from the larger codebase, presenting only the relevant details to developers rather than requiring them to manually investigate entire source files
3Productivity
If automated AI system is used, then debugging time is reduced and accuracy is improved, but the system complexity increases
Solution Approach 1:
The AI-based debugging system is designed to handle multiple types of errors, programming languages, and code structures through a single unified platform, providing versatile debugging capabilities without requiring separate specialized tools for each scenario
Data Source
AI summary
Examples of the present disclosure describe systems and methods for automatically detecting and repairing reliability issues in operating systems and applications using a generative artificial intelligence (“AI”) system. In examples, a generative AI system receives a request to evaluate a detected issue in a software service or application. In response, the system analyzes error information associated with the detected issue to build an error context for the software code that caused the detected issue. The error context is used to identify the location of the software code file that comprises the software code. The error context and the software code file are used to identify a prompt. The prompt, the error context, and/or the identified software code are provided as input to a language model. The language model provides an output that is responsive to the user request and may perform actions to further evaluate or repair the detected issue.