
Hagar Gomaa developed and refactored core features across Stockholm-Squad’s Plan-Mate, Finance-Tracker, and Food-Change-Mood repositories, focusing on backend reliability, data integrity, and user experience. She implemented transaction viewing with robust ID validation in Finance-Tracker and delivered an easy meal suggestion engine in Food-Change-Mood, integrating CSV parsing and error handling. In Plan-Mate, Hagar expanded authentication coverage, built an end-to-end user onboarding flow with password hashing, and led broad codebase and data model refactors to improve maintainability. Her work leveraged Java, Kotlin, and test-driven development, resulting in cleaner architecture, stronger test infrastructure, and more reliable, data-driven application workflows.

May 2025 performance summary for Stockholm-Squad/Plan-Mate. Delivered a broad Core Codebase Refactor, Data Models Refactor, and extensive mapping enhancements, along with UI refinements and tests. Implemented Audit System Mapper Enhancement and additional mappers for application state and tasks. A critical bug fix addressed state handling and merge conflicts, stabilizing edit/delete workflows. Result: improved maintainability, data integrity, and UI reliability; faster, safer feature delivery; stronger test coverage and infrastructure. Technologies/skills demonstrated include large-scale refactoring, data modeling and mapping patterns, repository layer alignment, UI testing, local datetime handling, and test infrastructure.
May 2025 performance summary for Stockholm-Squad/Plan-Mate. Delivered a broad Core Codebase Refactor, Data Models Refactor, and extensive mapping enhancements, along with UI refinements and tests. Implemented Audit System Mapper Enhancement and additional mappers for application state and tasks. A critical bug fix addressed state handling and merge conflicts, stabilizing edit/delete workflows. Result: improved maintainability, data integrity, and UI reliability; faster, safer feature delivery; stronger test coverage and infrastructure. Technologies/skills demonstrated include large-scale refactoring, data modeling and mapping patterns, repository layer alignment, UI testing, local datetime handling, and test infrastructure.
April 2025: Delivered key features across three repos with a focus on reliability, UX, and business value. Finance-Tracker introduced Transaction Viewing with robust ID validation, consolidating input validation to reduce user errors and improve data integrity. Food-Change-Mood added Easy Meal Suggestions via GetEasyFoodSuggestionsUseCase, including repository/UI/CSV integration, up to 10 shuffled results, and strong error handling when no suggestions are found. Plan-Mate released two major streams: expanded authentication test coverage to strengthen security and reliability, and an end-to-end Add User flow (UseCase, UI, persistence) with password hashing and thorough tests. Across projects, enhancements to test infrastructure and targeted refactors improved maintainability and code quality. These changes enhance user confidence, reduce error-prone workflows, and accelerate onboarding and data-driven decisions by delivering reliable, well-tested functionality.
April 2025: Delivered key features across three repos with a focus on reliability, UX, and business value. Finance-Tracker introduced Transaction Viewing with robust ID validation, consolidating input validation to reduce user errors and improve data integrity. Food-Change-Mood added Easy Meal Suggestions via GetEasyFoodSuggestionsUseCase, including repository/UI/CSV integration, up to 10 shuffled results, and strong error handling when no suggestions are found. Plan-Mate released two major streams: expanded authentication test coverage to strengthen security and reliability, and an end-to-end Add User flow (UseCase, UI, persistence) with password hashing and thorough tests. Across projects, enhancements to test infrastructure and targeted refactors improved maintainability and code quality. These changes enhance user confidence, reduce error-prone workflows, and accelerate onboarding and data-driven decisions by delivering reliable, well-tested functionality.
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