uprm-inso4101-2024-2025-s2/semester-project--uprm-lost-and-found
Mar 2025 – Mar 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
Backend DevelopmentDatabase DesignDatabase ManagementSQLAlchemy
armanskL
PROFILE
Armanskl
Developed core discovery and matching functionality for the Lost & Found system in the uprm-inso4101-2024-2025-s2/semester-project--uprm-lost-and-found repository, focusing on backend development and database design. Built a Matches table and corresponding SQLAlchemy model to track potential matches between lost and found items, incorporating confidence scores and status fields for improved triage. Enhanced search and filtering capabilities allowed users and staff to query items by name, category, location, date, or recency, with results ordered chronologically. Leveraged Python and SQL to ensure a maintainable, auditable data model that supports higher match rates and streamlined recovery workflows for end users.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
85
Activity Months1
Your Network
192 peopleWork History
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025: Delivered core discovery and matching capabilities for the Lost & Found system, significantly improving how users discover items and how staff triage potential matches. Key features include a Matches table with confidence scoring, and robust search and filtering across lost and found items with chronological result ordering. These changes lay the groundwork for higher match rates and faster recovery workflows, while maintaining a clean data model and clear auditability.
2 Commits • 1 Features
Mar 1, 2025March 2025: Delivered core discovery and matching capabilities for the Lost & Found system, significantly improving how users discover items and how staff triage potential matches. Key features include a Matches table with confidence scoring, and robust search and filtering across lost and found items with chronological result ordering. These changes lay the groundwork for higher match rates and faster recovery workflows, while maintaining a clean data model and clear auditability.
March 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
Backend DevelopmentDatabase DesignDatabase ManagementSQLAlchemy
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