agarasia/SER516_Spring25_Teams_3_and_4_Backend
Apr 2025 – Apr 2025
1 Month active
Languages Used
DockerfilePython
Technical Skills
API DevelopmentBackend DevelopmentDockerGit
Jeteish Pratap Singh
PROFILE
Jeteish Pratap Singh
During April 2025, Jsing162 developed backend enhancements for the agarasia/SER516_Spring25_Teams_3_and_4_Backend repository, focusing on automating the LCOMHS scoring workflow. They implemented a new API endpoint using Python and Docker, enabling automated calculation of LCOMHS scores for Java classes based on a simple JSON input containing a repository URL. The service was refactored to leverage a shared repository cloning mechanism, utilizing pre-cloned repositories on a shared volume to streamline setup and integration. This approach reduced manual intervention, facilitated smoother CI/CD pipeline integration, and established a reusable foundation for automated scoring across multiple teams, demonstrating thoughtful backend engineering.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
272
Activity Months1
Your Network
67 peopleWork History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025: Delivered backend enhancements for the LCOMHS scoring workflow in agarasia/SER516_Spring25_Teams_3_and_4_Backend. Implemented a new LCOMHS scoring API and migrated to a shared repository cloning mechanism with pre-cloned repos on a shared volume, enabling streamlined, automated scoring for Java classes via a simple JSON input (repository URL) and a structured score output. This work reduces manual setup, accelerates integration with CI/CD pipelines, and lays groundwork for broader reuse across teams.
1 Commits • 1 Features
Apr 1, 2025April 2025: Delivered backend enhancements for the LCOMHS scoring workflow in agarasia/SER516_Spring25_Teams_3_and_4_Backend. Implemented a new LCOMHS scoring API and migrated to a shared repository cloning mechanism with pre-cloned repos on a shared volume, enabling streamlined, automated scoring for Java classes via a simple JSON input (repository URL) and a structured score output. This work reduces manual setup, accelerates integration with CI/CD pipelines, and lays groundwork for broader reuse across teams.
April 2025
Activity
Loading activity data...
Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
DockerfilePython
Technical Skills
API DevelopmentBackend DevelopmentDockerGit
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline