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
In April 2025, Jay Singh developed backend enhancements for the agarasia/SER516_Spring25_Teams_3_and_4_Backend repository, focusing on automating the LCOMHS scoring workflow. He 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. Jay refactored the service to leverage a shared repository cloning mechanism, utilizing pre-cloned repositories on a shared volume to streamline setup and facilitate integration with CI/CD pipelines. This work improved automation, reduced manual intervention, and established a foundation for broader reuse across development teams, demonstrating solid backend engineering skills.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
272
Activity Months1
Your Network
65 people
Work 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
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
DockerfilePython
Technical Skills
API DevelopmentBackend DevelopmentDockerGit
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