Static Analysis Visualization for Code Quality Metrics
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Solution Overview
Problem
Current static analysis systems lack effective visualization tools for software project and contributor activity, making it difficult to assess productivity and quality, and fail to efficiently identify characteristic segments of source code across multiple projects.
Innovation Solution
A static analysis system generates graphical user interface presentations to visualize quality and quantity metrics over time, and implements crowd-sourcing of queries to identify characteristic segments of source code, allowing multiple users to share and execute queries across projects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static analysis systems analyze source code to identify coding defects, then code quality measurement is improved, but the ability to visualize project and contributor activity effectively deteriorates
Solution Approach 1:
The patent transforms static code quality data into dynamic visual representations by adding the dimension of time and spatial organization. Graphical user interface presentations display code quality metrics, contributor activity, and project statistics across multiple dimensions (time series, spatial distribution, hierarchical structures), enabling effective visualization of previously abstract data without compromising measurement precision.
2Measurement precision
If static analysis systems use collection of rules to identify coding defects, then code quality assessment is improved, but the efficiency of identifying characteristic segments across multiple projects deteriorates
Solution Approach 1:
The patent creates a universal query execution engine that can apply the same static analysis rules across multiple projects simultaneously. The system allows users to define queries using query languages (Datalog, SQL) that can be executed against any number of projects, making the code quality assessment mechanism universally applicable and significantly improving identification efficiency across project portfolios.
Solution Approach 2:
The patent implements query sharing and replication mechanisms where a query defined for one project can be copied and executed against multiple other projects. This allows efficient reuse of analysis logic across projects, maintaining measurement precision while dramatically improving productivity through query replication and shared execution.
3Reliability
If static analysis systems generate alerts for coding defects, then code quality feedback is improved, but the ease of understanding team performance and productivity deteriorates
Solution Approach 1:
The patent employs color-coded visual representations in graphical user interface presentations to indicate different aspects of code quality and contributor performance. Different colors represent different metric values, contribution levels, and quality states, making team performance and productivity immediately understandable through visual cues rather than requiring detailed analysis of raw alert data.
Solution Approach 2:
The patent transforms one-dimensional alert data into multi-dimensional visual presentations that organize code quality feedback by contributor, time period, project, and metric type. This dimensional transformation makes team performance patterns, trends, and comparisons easily visible and understandable, converting reliable but complex feedback into intuitive visual insights.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for presenting static analysis user interface presentations. One of the methods includes receiving, from a user, a request for a user interface presentation representing multiple properties of source code snapshots committed to a project versus time. A plurality of snapshots are obtained for the project, wherein each snapshot comprises a representation of source code for the project at a respective time period. Multiple snapshot metrics are computed for each snapshot, including a net violation count and a count of lines of code added or removed. A graphical user interface presentation is generated that correlates periodic lines of code metrics with overall violation metrics.