Source Code Search Engine Syntax-Based Ranking
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Solution Overview
Problem
Existing source code search engines rank search results based on keyword frequency, which is less relevant for structured programming languages, leading to unsorted and less relevant search results for developers.
Innovation Solution
A system that generates metadata for source code files, associating each word with its code type based on the programming language's syntax, and uses a ranking engine to weight occurrences by code type and file type boost values, producing a syntax-based ranking order for more relevant search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If search results are ranked based on keyword frequency, then the ranking process is simple and fast, but the search results are less relevant for structured programming languages
Solution Approach 1:
The patent changes the ranking parameters from simple keyword frequency to a multi-dimensional scoring system that includes code type context (declaration, definition, usage), file type weights, and occurrence patterns. This transforms the ranking mechanism to better suit structured programming languages while maintaining computational feasibility through predefined weightings and systematic evaluation criteria.
Solution Approach 2:
The ranking system is segmented into multiple independent evaluation components: code type identification (declaration/definition/usage), file type classification, occurrence frequency analysis, and contextual positioning. Each segment evaluates specific aspects of code matches independently, then combines results to produce the final ranking, making the complex system manageable and interpretable.
2Ease of operation
If search results are unsorted, then the ranking process is simple, but navigating through search results becomes difficult and frustrating
Solution Approach 1:
The system changes from no sorting to sorting based on multiple parameters including code type relevance, file type importance, occurrence frequency, and contextual position. These parameters are weighted and combined to generate a comprehensive relevance score that automatically orders results, improving navigation without requiring complex user intervention.
Solution Approach 2:
The system performs preliminary ranking and sorting of search results before presentation to the user. By pre-processing results according to established criteria (code type weights, file type priorities, occurrence patterns), the system prepares optimized, relevance-ordered results in advance, making navigation intuitive and reducing user cognitive load during result exploration.
Data Source
AI summary
A syntax-based ranking technique is provided that ranks search results from multiple source code files in an order that considers the relevance of each matched term with a corresponding code type and the relevance of the type of file that contains the matched term. Boost values are provided for each code type of a matched term in order to weigh certain occurrences of the matched term with more relevance. Boost values are provided for each type of file that contains the matched term in order to weigh the occurrence of the term in a particular file with more relevance.