Chatbot Source Code Analysis for Error Diagnostics
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Solution Overview
Problem
Chatbots face difficulties in providing accurate responses to user queries about error codes when the error codes are not clearly represented in existing knowledge bases, leading to incomplete and outdated knowledge bases that require time-consuming human documentation efforts.
Innovation Solution
A method where a chatbot automatically reviews the source code of a software product to identify relevant information for formulating answers to user queries, allowing it to determine responses without comprehensive human-prepared documentation, thereby reducing system costs and increasing speed and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a chatbot uses an existing knowledge base to respond to user queries about error codes, then response time is fast, but the knowledge base becomes incomplete and outdated requiring time-consuming human documentation efforts
Solution Approach 1:
The chatbot automatically extracts error code information from the software product's source code without requiring human documentation. The system parses the program code to identify error codes, their meanings, and related diagnostic information, enabling the chatbot to maintain and update its knowledge base autonomously.
Solution Approach 2:
The system pre-processes the software product's source code to extract and structure error code information before it is needed for user queries. This preliminary extraction creates a comprehensive knowledge base that the chatbot can query efficiently, avoiding the need for reactive human documentation.
2Reliability
If comprehensive human documentation is prepared for error codes, then knowledge base completeness improves, but system cost and documentation time increase
Solution Approach 1:
The patent replaces the manual mechanical process of human documentation with an automated computational process. The chatbot uses program parsing and natural language processing to extract error code information from source code, substituting human effort with automated text analysis and code interpretation.
Solution Approach 2:
The system copies error code information directly from the software product's source code and comments, preserving the original diagnostic information while making it accessible to users. This copying approach ensures accuracy while eliminating the need for separate human documentation efforts.
3Measurement precision
If the chatbot reviews source code automatically to identify error information, then response accuracy improves, but processing complexity increases
Solution Approach 1:
The patent introduces an intermediary layer that translates complex source code analysis into structured error code information. The chatbot uses natural language processing and program parsing to bridge the gap between raw code and user-friendly error explanations, managing complexity while maintaining accuracy.
Data Source
AI summary
Aspects of the present invention disclose a method, computer program product, and system for determining a response to a query from a user. The method includes one or more processors receiving a query associated with a software product. The query includes an indication of an error. The method further includes one or more processors determining whether a response to the query is available in an accessible knowledge base. In response to determining that a response to the query is not available, the method further includes one or more processors identifying content in program code of the software product that corresponds to the indicated error of the received query. The method further includes one or more processors determining a response to the query based on the identified content in the program code. The determined response to the query includes diagnostic information corresponding to the indicated error.