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
Armando Rivera developed core discovery and matching features for the uprm-inso4101-2024-2025-s2/semester-project--uprm-lost-and-found repository, focusing on backend development and database design using Python and SQLAlchemy. He introduced a Matches table and corresponding data model to track potential lost and found item matches, incorporating confidence scoring and status fields to support triage workflows. Armando also implemented robust search and filtering capabilities, enabling queries by name, category, location, and date, with results ordered chronologically. His work emphasized maintainable data modeling and clear repository-level documentation, laying a solid foundation for scalable, auditable matching and recovery processes within the system.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
85
Activity Months1
Your Network
180 people
Work 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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