Monash-FIT3170/2025W2-FindingNibbles
May 2025 – May 2025
1 Month active
Languages Used
C++DartJavaScriptObjective-CSwiftTypeScriptXML
Technical Skills
API DevelopmentAPI IntegrationBackend DevelopmentCocoaPodsCode RefactoringData Transfer Objects
bmat0014
PROFILE
Bmat0014
Contributed to Monash-FIT3170/2025W2-FindingNibbles by delivering both backend and frontend enhancements for restaurant discovery, focusing on accurate data retrieval and improved user interaction. Developed a Restaurant API with cuisine filtering using TypeScript and NestJS, consolidating services and introducing Data Transfer Objects for maintainability. On the frontend, implemented map-based restaurant markers in Flutter, ensuring seamless integration with backend data and interactive UI elements. Addressed critical bugs related to map bounds and data access, while refining the user interface with color-coded filtering chips and improved formatting. Emphasized code quality through refactoring, infrastructure setup with CocoaPods, and comprehensive code cleanup.
Overall Statistics
Feature vs Bugs
38%Features
Repository Contributions
21Total
Bugs
5
Commits
21
Features
3
Lines of code
2,295
Activity Months1
Your Network
139 peopleSame Organization
@student.monash.edu118
Work History
May 2025
21 Commits • 3 Features
May 1, 2025May 2025 monthly summary for Monash-FIT3170/2025W2-FindingNibbles: Delivered backend and frontend restaurant discovery enhancements, fixed critical data retrieval issues, and strengthened project infrastructure and code quality to support faster onboarding and sustainable maintenance. Key outcomes include: Backend: Implemented Restaurant API resource and cuisine filtering with CuisineDto, enabling filtering by cuisine and minimum rating. Frontend: Implemented restaurant markers on map, with skeleton, loading behavior, and interactive info on click; markers wired to backend data and displayed on map load. Map bounds: Fixed backend interaction and ensure findAll operates correctly within map bounds. Infra/UI: Podfiles added for project setup; UI filtering popup formatting improved and color-coded filtering chips; code cleanup and formatting fixes. Impact: Improved restaurant discovery accuracy, faster user interaction, and a cleaner, more maintainable codebase that reduces onboarding effort for new contributors.
21 Commits • 3 Features
May 1, 2025May 2025 monthly summary for Monash-FIT3170/2025W2-FindingNibbles: Delivered backend and frontend restaurant discovery enhancements, fixed critical data retrieval issues, and strengthened project infrastructure and code quality to support faster onboarding and sustainable maintenance. Key outcomes include: Backend: Implemented Restaurant API resource and cuisine filtering with CuisineDto, enabling filtering by cuisine and minimum rating. Frontend: Implemented restaurant markers on map, with skeleton, loading behavior, and interactive info on click; markers wired to backend data and displayed on map load. Map bounds: Fixed backend interaction and ensure findAll operates correctly within map bounds. Infra/UI: Podfiles added for project setup; UI filtering popup formatting improved and color-coded filtering chips; code cleanup and formatting fixes. Impact: Improved restaurant discovery accuracy, faster user interaction, and a cleaner, more maintainable codebase that reduces onboarding effort for new contributors.
May 2025
Activity
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Quality Metrics
Correctness84.8%
Maintainability83.4%
Architecture77.2%
Performance76.6%
AI Usage21.0%
Skills & Technologies
Programming Languages
C++DartJavaScriptObjective-CSwiftTypeScriptXML
Technical Skills
API DevelopmentAPI IntegrationBackend DevelopmentCocoaPodsCode RefactoringData Transfer ObjectsDatabase QueryingFlutterFrontend DevelopmentGeolocationHTTP RequestsMap IntegrationMobile DevelopmentNestJSPrisma
Repositories Contributed To
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