Software Project Similarity Grouping for Visualization
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Solution Overview
Problem
As the number of software development projects grows, visualizing their similarities through static analysis becomes increasingly incomprehensible, reducing usability for end users and requiring the processing and transmission of excessive data.
Innovation Solution
A system computes similarity groupings for software development projects based on analysis metrics such as snapshot and functionality metrics, allowing for focused comparisons and user interface presentations that rank and cluster similar projects, thereby simplifying data presentation and reducing data processing needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of projects to be compared is increased, then the comprehensiveness of analysis is improved, but the visualization becomes incomprehensible and usability deteriorates
Solution Approach 1:
The patent segments the large set of projects into smaller similarity groups based on computed similarity metrics. Instead of presenting all projects in a single visualization, the system divides them into manageable clusters where each cluster contains projects with similar characteristics, making the visualization comprehensible while maintaining comprehensive analysis capability across multiple groups.
Solution Approach 2:
The patent extracts a subset of most similar projects from the complete project set and presents them separately. By taking out the most relevant projects (those with highest similarity scores) and presenting them in a focused view, the system maintains comprehensiveness by preserving access to the full dataset while improving usability through selective presentation of the most pertinent comparisons.
2Reliability
If all projects are included in comparisons, then the completeness of data is improved, but the amount of data processing and transmission increases
Solution Approach 1:
The patent extracts only the necessary subset of projects (most similar ones) for detailed comparison and transmission to the user interface. By computing similarity metrics for all projects to maintain completeness, then extracting and transmitting only the relevant subset for actual comparison, the system preserves data completeness while significantly reducing processing and transmission overhead.
Solution Approach 2:
The patent performs partial action by computing full similarity metrics for all projects (excessive computation) but only transmitting and displaying results for the most similar subset (partial transmission). This approach ensures completeness of analysis while optimizing productivity by avoiding unnecessary transmission and rendering of all project data.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating similarity groupings of software projects. One of the methods includes computing respective values for a plurality of analysis metrics associated with each software development project of a plurality of software development projects, wherein the analysis metrics include snapshot metrics that represent respective properties of the commit history of snapshots in the software development project, functionality metrics that represent respective properties of software elements in the software development project, or both. A similarity grouping is computed for the primary software development project based on the respective computed values for the plurality of analysis metrics for the plurality of software development projects, wherein the similarity grouping for the primary software development project comprises fewer than all of the plurality of software development projects.