Developer Tool Query Response Using Semantic Code Chunk Highlighting
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Solution Overview
Problem
Conventional developer tools rely on exact string matching for code search, lacking the ability to highlight semantically related keywords in relevant code chunks, which hinders efficient code development and increases resource consumption.
Innovation Solution
A system that parses a codebase into chunks and identifies semantically related keywords, generating a visual representation that highlights these keywords in relevant code chunks to provide context for user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exact string matching is used for code search, then search precision is improved, but productivity deteriorates due to lack of semantic understanding and manual review time
Solution Approach 1:
The patent replaces traditional mechanical exact string matching with an AI-based semantic analysis system. The AI model understands the meaning and context of code elements, enabling developers to search using natural language or conceptual terms rather than requiring precise syntax matching, thereby improving both search precision and development productivity
Solution Approach 2:
The system changes the search parameter from exact string matching to semantic similarity scoring. By implementing a relevancy criterion based on AI-generated scores, the system identifies code chunks that are semantically related to the query, providing more accurate and useful search results that improve productivity
2Ease of operation
If semantic keyword highlighting is implemented in code chunks, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The patent extracts and highlights only the most relevant semantically related keywords within code chunks rather than displaying or processing the entire codebase. This selective extraction provides contextual information to help developers quickly understand why a code chunk is relevant, improving ease of operation while managing complexity through focused processing
Solution Approach 2:
The system introduces an intermediary AI model that acts as a mediator between the user query and the codebase. This AI intermediary performs semantic analysis, identifies relevant keywords, and generates highlights, thereby improving code navigation ease while encapsulating the complexity within a dedicated component rather than throughout the entire system
3Measurement precision
If AI model is used to identify semantically related keywords, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent applies partial action by using the AI model selectively only for identifying semantically related keywords in the most relevant code chunks, rather than processing the entire codebase uniformly. The system first identifies highly relevant chunks using efficient filtering, then applies the energy-intensive AI analysis only where needed, thereby improving keyword relevance precision while managing computational energy consumption
Data Source
AI summary
Techniques are described herein that are capable of responding to a query in a developer tool using semantically related keywords in relevant code chunks. A user-generated query regarding a location of an element in a codebase of a software development project is received. The codebase is parsed into code chunks. Semantically related keywords, including keywords from the user-generated query and other keywords that are semantically related to the keywords, are identified. Relevant code chunks are selected from the code chunks based on satisfaction of a relevancy criterion regarding the user-generated query. Execution of an instruction is triggered, which causes a visual representation of a response to the user-generated query to be generated. The execution of the instruction causes the visual representation to include at least portions of the relevant code chunks and further causes at least a subset of the semantically related keywords to be highlighted in the portions.