
Over a two-month period, contributed to the agarasia/SER516_Spring25_Teams_3_and_4_Backend repository by developing and enhancing a Dockerized Afferent Coupling API service that computes coupling metrics for Java classes and exposes results via a REST API. Improved deployment consistency and operational readiness through Docker Compose, CI/CD pipelines using GitHub Actions, and comprehensive documentation. Refactored backend services to remove MongoDB dependencies and introduced token-based access for private repositories, while expanding automated test coverage and improving error handling. Also supported frontend reliability by implementing automated CI/CD workflows. Work utilized Java, Python, Docker, and Spring Boot, emphasizing maintainability, deployment speed, and code quality.
April 2025 monthly summary for SER516 Teams 3 & 4 across Backend and Frontend. The month delivered a cohesive set of feature enhancements, reliability improvements, and expanded CI/CD coverage that directly increases deployment speed, quality, and maintainability. Key backend work focused on Afferent coupling service improvements, Docker Compose and README updates, MongoDB removal with token-based access for private repos, and expanded test coverage. Frontend introduced an automated CI/CD workflow with Node.js setup, dependency caching fixes, and reliability improvements in GitHub Actions. The team also implemented CI workflows for Efferent Coupling, Defect Density, and Python services, along with documentation and Dockerfile updates. In parallel, multiple bug fixes improved stability and test reliability, including LCOM4/LCOMHS test fixes and Defect Score service tests, as well as CI workflow corrections. This combination reduces build failures, accelerates deployment, and enhances cross-team collaboration through standardized tooling and documentation.
April 2025 monthly summary for SER516 Teams 3 & 4 across Backend and Frontend. The month delivered a cohesive set of feature enhancements, reliability improvements, and expanded CI/CD coverage that directly increases deployment speed, quality, and maintainability. Key backend work focused on Afferent coupling service improvements, Docker Compose and README updates, MongoDB removal with token-based access for private repos, and expanded test coverage. Frontend introduced an automated CI/CD workflow with Node.js setup, dependency caching fixes, and reliability improvements in GitHub Actions. The team also implemented CI workflows for Efferent Coupling, Defect Density, and Python services, along with documentation and Dockerfile updates. In parallel, multiple bug fixes improved stability and test reliability, including LCOM4/LCOMHS test fixes and Defect Score service tests, as well as CI workflow corrections. This combination reduces build failures, accelerates deployment, and enhances cross-team collaboration through standardized tooling and documentation.
March 2025: Delivered the Afferent Coupling API Service for the agarasia/SER516_Spring25_Teams_3_and_4_Backend repository. The service computes afferent coupling for Java classes in a repository and exposes the results via a REST API. The solution is Dockerized with a dedicated Dockerfile and documented to simplify deployment, testing, and onboarding. No high-severity bugs were reported this month; the focus was on feature delivery and operational readiness. Business value: provides automated, API-accessible coupling metrics to inform modularization decisions, architectural reviews, and health checks, reducing time-to-insight and enabling data-driven refactors. Technologies demonstrated include Java-based service development, REST API design, Docker containerization, and clear documentation for usage and deployment.
March 2025: Delivered the Afferent Coupling API Service for the agarasia/SER516_Spring25_Teams_3_and_4_Backend repository. The service computes afferent coupling for Java classes in a repository and exposes the results via a REST API. The solution is Dockerized with a dedicated Dockerfile and documented to simplify deployment, testing, and onboarding. No high-severity bugs were reported this month; the focus was on feature delivery and operational readiness. Business value: provides automated, API-accessible coupling metrics to inform modularization decisions, architectural reviews, and health checks, reducing time-to-insight and enabling data-driven refactors. Technologies demonstrated include Java-based service development, REST API design, Docker containerization, and clear documentation for usage and deployment.

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