Artifact Version Tag Matching for Source Commit Identification
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Solution Overview
Problem
Challenges exist in tracking libraries and library versions in large software projects due to dynamic updates and inconsistencies in tag identification, leading to difficulties in determining security vulnerabilities and outdated versions.
Innovation Solution
A method and system utilizing a fuzzy regular expression generator to process artifact version identifiers and commit repository tags, enabling accurate selection of matching tags and commits through a scoring system to identify corresponding commits in the target software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If developers dynamically update library versions and modify source code, then software development flexibility and productivity are improved, but tracking accuracy and version identification reliability deteriorate
Solution Approach 1:
The system performs preliminary actions by generating fuzzy regular expressions from artifact version identifiers before tag matching occurs. This pre-computation of flexible matching patterns enables the system to accommodate dynamic version updates while maintaining accurate tracking, as the fuzzy expressions are designed to handle variations in version numbering schemes that developers may introduce during dynamic updates.
Solution Approach 2:
The invention changes the parameter of tag matching from exact matching to fuzzy matching using regular expressions. By transforming the matching criterion from a rigid parameter (exact string equality) to a flexible parameter (pattern matching with tolerance for variations), the system can accommodate dynamic version updates and inconsistent tagging while maintaining reliable version identification.
2Measurement precision
If fuzzy regular expression matching is used to handle tag variations, then tag matching accuracy is improved, but processing complexity increases
Solution Approach 1:
The system segments the tag matching process into distinct stages: generating fuzzy regular expressions from artifact version identifiers, processing tags through the regex patterns, filtering matching results, and selecting the top matching tag. This segmentation of the complex fuzzy matching process into manageable steps reduces processing complexity while maintaining high matching accuracy.
Solution Approach 2:
The system applies partial action by processing only the subset of tags that match the fuzzy regular expression patterns, rather than performing exhaustive comparisons with all tags. By filtering tags through regex matching first and then selecting only the top matches, the system reduces the overall processing load while maintaining accuracy for the most relevant tags.
Data Source
AI summary
Artifact source code identification includes obtaining an artifact version identifier of an artifact in an artifact repository, generating, by a fuzzy regular expression generator, an artifact version identifier regular expression from the artifact version identifier for the artifact version, and processing, with the artifact version identifier regular expression, tags in a commit repository to select a subset of the tags. Artifact source code identification further includes selecting a top matching tag from the subset and obtaining a commit corresponding to the top matching tag.