
Developed and delivered analytics-focused backend features for dungkhmt/openerp-micro-service, building a User Submissions API and a Contest Submission Analytics pipeline for programming contests. Leveraged Java and Spring Boot to design endpoints that aggregate and structure per-user submission data, including total, accepted, and compile error counts, supporting downstream analytics and dashboard integration. Implemented logic to process and categorize new submissions by status, ensuring up-to-date metrics for organizers and participants. Focused on API consistency, extensibility, and data reliability, with all work traceable via git commits. Demonstrated skills in API development, backend microservices, and database management, enabling scalable, user-centric contest analytics.
Month 2024-12: Delivered Contest Submission Analytics: User Submission Counts feature for dungkhmt/openerp-micro-service. Implemented end-to-end pipeline to track and store per-user submission counts, process new submissions, categorize by status (accepted vs compile error), and update metrics with total, accepted, and failed counts for analytics and dashboards. No major bugs fixed documented; focus on feature delivery and data reliability. Impact: Enables accurate, per-user contest analytics and informed decision-making for organizers and participants; improves dashboard readiness and data quality. Technologies/skills demonstrated: backend microservice development, Python data processing, per-user aggregation, status-based analytics, and git-based traceability (commit 38999b4f48c6581569a60a5cedf4f95ab2b19414).
Month 2024-12: Delivered Contest Submission Analytics: User Submission Counts feature for dungkhmt/openerp-micro-service. Implemented end-to-end pipeline to track and store per-user submission counts, process new submissions, categorize by status (accepted vs compile error), and update metrics with total, accepted, and failed counts for analytics and dashboards. No major bugs fixed documented; focus on feature delivery and data reliability. Impact: Enables accurate, per-user contest analytics and informed decision-making for organizers and participants; improves dashboard readiness and data quality. Technologies/skills demonstrated: backend microservice development, Python data processing, per-user aggregation, status-based analytics, and git-based traceability (commit 38999b4f48c6581569a60a5cedf4f95ab2b19414).
In 2024-11, delivered a new User Submissions API for programming contests in dungkhmt/openerp-micro-service. The API provides endpoints to retrieve per-user submissions with aggregates (total, accepted, compile errors) and uses a structured response model to simplify downstream analytics. No major bugs were reported this month; focus was on feature delivery and API design to enable contest analytics, dashboards, and potential leaderboards. This work strengthens the platform's ability to support user-centric analytics and scalable reporting across contests.
In 2024-11, delivered a new User Submissions API for programming contests in dungkhmt/openerp-micro-service. The API provides endpoints to retrieve per-user submissions with aggregates (total, accepted, compile errors) and uses a structured response model to simplify downstream analytics. No major bugs were reported this month; focus was on feature delivery and API design to enable contest analytics, dashboards, and potential leaderboards. This work strengthens the platform's ability to support user-centric analytics and scalable reporting across contests.

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