
Worked on the DEFRA/epr-pom-func-producer-validation repository to enhance validation logic for zero-returns scenarios in packaging material weight reporting. Developed and integrated support for zero returns on QuantityKg, introducing a new warning code and updating backend validators to ensure accurate error handling. Addressed a critical bug affecting zero-return validation and error-code correctness for both quantity and unit fields, expanding unit test coverage to improve reliability. Utilized C#, Java, and JUnit for validator development and testing, while also implementing code quality improvements based on SonarQube feedback. These changes improved data integrity, compliance, and efficiency in producer validation workflows.
March 2025 — Monthly work summary for DEFRA/epr-pom-func-producer-validation. Delivered critical validation enhancements and robustness improvements for zero-returns scenarios. Key features delivered: Zero returns support for packaging material weight (QuantityKg) with new warning code 61, updated validation logic, and unit tests. Major bugs fixed: Zero-return validation and error-code correctness for QuantityKg and QuantityUnits; corrected error codes and expanded validator test coverage; significant test coverage improvements and code quality fixes (SonarQube). Overall impact: improved data integrity, compliance with zero-returns policy, reduced downstream validation failures, and faster producer validation cycles. Technologies/skills demonstrated: Java/Kotlin validators, JUnit-based unit testing, SonarQube/code-coverage improvements, CI readiness.
March 2025 — Monthly work summary for DEFRA/epr-pom-func-producer-validation. Delivered critical validation enhancements and robustness improvements for zero-returns scenarios. Key features delivered: Zero returns support for packaging material weight (QuantityKg) with new warning code 61, updated validation logic, and unit tests. Major bugs fixed: Zero-return validation and error-code correctness for QuantityKg and QuantityUnits; corrected error codes and expanded validator test coverage; significant test coverage improvements and code quality fixes (SonarQube). Overall impact: improved data integrity, compliance with zero-returns policy, reduced downstream validation failures, and faster producer validation cycles. Technologies/skills demonstrated: Java/Kotlin validators, JUnit-based unit testing, SonarQube/code-coverage improvements, CI readiness.

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