Incremental Code Coverage Analyzer for Multi-Team Software Projects
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Solution Overview
Problem
Existing systems fail to provide accurate incremental code coverage for individual software projects in multi-team environments, leading to inaccurate reporting and inability to segregate changes made by different teams working on the same module, and do not calculate mutation coverage in a project-wise manner.
Innovation Solution
A system and method for determining project-specific incremental code coverage by integrating an incremental code/mutation coverage analyzer engine with project management and version control software, allowing parallel computation of delta coverage across multiple projects, and segregating changes made by different teams, using changelists and code coverage data from libraries like JACOCO and pitest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems calculate code coverage for entire source code, then comprehensive coverage information is obtained, but incremental coverage for individual projects cannot be determined
Solution Approach 1:
The system segments the monolithic code coverage measurement into project-specific incremental measurements. By dividing the overall codebase into individual software projects and calculating coverage changes for each project separately, the system enables precise measurement of incremental coverage without losing project-specific information.
Solution Approach 2:
The system extracts incremental coverage information from the comprehensive code coverage data by identifying and isolating changes specific to individual projects. This extraction process separates project-specific coverage metrics from the overall codebase coverage, enabling focused analysis of incremental changes.
2Productivity
If multiple project teams work on the same module simultaneously, then development productivity increases, but code coverage reporting becomes inaccurate and cannot segregate team-specific changes
Solution Approach 1:
The system segments code coverage tracking by project team and module, creating isolated measurement contexts for each team's changes. This segmentation allows multiple teams to work simultaneously on the same module while maintaining accurate, team-specific coverage reports that do not interfere with each other.
Solution Approach 2:
The system introduces an intermediary layer that tracks and attributes code changes to specific project teams before calculating coverage metrics. This intermediary mechanism mediates between multiple teams' concurrent modifications and the final coverage reporting, ensuring accurate attribution of changes to the correct teams.
3Adaptability or versatility
If legacy code is updated frequently to meet customer requirements, then software adaptability improves, but maintaining code quality becomes more difficult
Solution Approach 1:
The system implements feedback mechanisms that provide real-time incremental code coverage and mutation coverage metrics as legacy code is updated. This feedback loop enables development teams to immediately assess the impact of changes on code quality, allowing them to maintain reliability while adapting to new requirements.
Solution Approach 2:
The system performs preliminary analysis of code changes before they are fully integrated, calculating incremental coverage metrics to predict potential quality issues. This preliminary action allows teams to identify and address code quality concerns before they propagate through the legacy codebase.
Data Source
AI summary
A system, method, and computer program product are provided for determining incremental code coverage of a software project. In operation, a system provides computation of project specific incremental (delta) code coverage in parallel in scenarios of multiple project teams working on different projects on a same module (or in the same repository). Further, an incremental code/mutation coverage analyzer engine associated with the system may be integrated with a project management tool and a version control software to obtain the changed code lines with respect to each project, using what it calculates as the incremental code and/or the mutation coverage.