
Clare Ahn developed robust restaurant data retrieval and user-centric filtering workflows for the Monash-FIT3170/2025W2-FindingNibbles repository, focusing on both backend and frontend improvements. She enhanced the RestaurantService in Dart to support cuisine-based filtering, pagination, and sorting, and implemented a responsive HomePage UI in Flutter that allows users to filter restaurants by cuisine and minimum rating. Her work included state management refinements for smoother loading experiences and theme-based UI polish, addressing edge cases in dropdown population and filter chip styling. Clare’s contributions demonstrated depth in API integration, service layer implementation, and UI development, resulting in maintainable, user-friendly features.

May 2025 monthly summary highlighting key accomplishments, business impact, and technical delivery for Monash-FIT3170/2025W2-FindingNibbles. Focused on delivering robust restaurant data retrieval, user-centric UI filtering workflows, and UI polish, coupled with a performance-friendly loading refactor and targeted UI bug fixes.
May 2025 monthly summary highlighting key accomplishments, business impact, and technical delivery for Monash-FIT3170/2025W2-FindingNibbles. Focused on delivering robust restaurant data retrieval, user-centric UI filtering workflows, and UI polish, coupled with a performance-friendly loading refactor and targeted UI bug fixes.
Overview of all repositories you've contributed to across your timeline