
Irene Recio López developed the foundational Winery domain layer and REST API for the miw-upm/apaw-practice repository, enabling end-to-end winery operations and reliable QA environments. She designed core data models for evaluations, reservations, tasting sessions, and wines, integrating them with MongoDB and refactoring identifiers to use UUIDs. Leveraging Java and Spring Boot, Irene implemented DAOs, repositories, and a seeding strategy to ensure consistent development and test data. Her work included comprehensive API endpoints for managing sessions, reservations, wines, and pricing, along with robust search and batch update features. She also enhanced test automation, improving data consistency and coverage.

October 2025: Delivered foundational Winery domain layer and API, enabling end-to-end winery operations and reliable QA environments. Key contributions include establishing core data models (Evaluation, Reservation, TastingSession, Wine) with MongoDB mappings, UUID refactor, DAOs/Repositories, and seed data; implementing a comprehensive Winery REST API (endpoints for tasting sessions, reservations, wines, pricing, plus search) with robust tests; and QA improvements to stabilize tests and ensure consistent data setup. Business value: a scalable data foundation and API surface enabling faster feature delivery, reliable pricing updates, and repeatable test environments. Technical achievements: data modeling, repository pattern, seed strategy, REST API design, test automation, and search capabilities.
October 2025: Delivered foundational Winery domain layer and API, enabling end-to-end winery operations and reliable QA environments. Key contributions include establishing core data models (Evaluation, Reservation, TastingSession, Wine) with MongoDB mappings, UUID refactor, DAOs/Repositories, and seed data; implementing a comprehensive Winery REST API (endpoints for tasting sessions, reservations, wines, pricing, plus search) with robust tests; and QA improvements to stabilize tests and ensure consistent data setup. Business value: a scalable data foundation and API surface enabling faster feature delivery, reliable pricing updates, and repeatable test environments. Technical achievements: data modeling, repository pattern, seed strategy, REST API design, test automation, and search capabilities.
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