UngSangYoon/Algorithm_Study_FISA
Jan 2025 – Apr 2025
4 Months active
Languages Used
PythonGit
Technical Skills
AlgorithmBacktrackingCombinatoricsModular ArithmeticNumber TheoryPermutations
leetaemin
PROFILE
Leetaemin
Over four months, UngSangYoon developed a suite of algorithmic problem-solving tools in the UngSangYoon/Algorithm_Study_FISA repository, focusing on dynamic programming, combinatorics, and greedy algorithms using Python and Git for version control. He implemented reusable modules for tasks such as memory optimization, tiling, and meeting scheduling, emphasizing maintainable code and efficient data handling. His work included dynamic programming solutions for sequence generation, coin change, and grid pathfinding, as well as utilities for sorting and combinatorial calculations. The engineering approach prioritized modularity and extensibility, resulting in a robust foundation for algorithm practice and interview preparation without recorded bug fixes during the period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
28Total
Bugs
0
Commits
28
Features
21
Lines of code
876
Activity Months4
Your Network
27 people
Work History
April 2025
4 Commits • 3 Features
Apr 1, 2025April 2025 highlights for UngSangYoon/Algorithm_Study_FISA: Delivered three core features using DP/greedy approaches—Memory Deactivation Optimization for App Memory, Tile Filling DP Algorithms, and Meeting Room Scheduling Script. These efforts reduce memory management costs, improve solution efficiency for tiling problems, and automate non-overlapping meeting planning. The work included refactoring for readability and maintainability across DP modules, and produced production-ready Python scripts. Key commits include 74b7d1118105f095837ebdae0d76d60550f9cbc2, bffb43ed9a70a9369abd023d9428a3bf988d2408, 30b4bfb1c7f184adbd464e12cdc1cc7ec96bd177, and c9a2c02003b1367f8ffd111ca8e2582c2cd9bf5e.
4 Commits • 3 Features
Apr 1, 2025April 2025 highlights for UngSangYoon/Algorithm_Study_FISA: Delivered three core features using DP/greedy approaches—Memory Deactivation Optimization for App Memory, Tile Filling DP Algorithms, and Meeting Room Scheduling Script. These efforts reduce memory management costs, improve solution efficiency for tiling problems, and automate non-overlapping meeting planning. The work included refactoring for readability and maintainability across DP modules, and produced production-ready Python scripts. Key commits include 74b7d1118105f095837ebdae0d76d60550f9cbc2, bffb43ed9a70a9369abd023d9428a3bf988d2408, 30b4bfb1c7f184adbd464e12cdc1cc7ec96bd177, and c9a2c02003b1367f8ffd111ca8e2582c2cd9bf5e.
April 2025
March 2025
12 Commits • 12 Features
Mar 1, 2025March 2025 (UngSangYoon/Algorithm_Study_FISA) delivered a focused set of dynamic programming and algorithmic solutions that expand testing coverage, improve problem-solving templates, and create reusable patterns for interview prep. With multi-test support, optimized DP approaches, and grid/backtracking techniques, the month established a solid foundation for scalable algorithm practice and future feature development. No major bugs fixed this month; development focused on feature delivery and correctness across tasks.
March 2025
12 Commits • 12 Features
Mar 1, 2025March 2025 (UngSangYoon/Algorithm_Study_FISA) delivered a focused set of dynamic programming and algorithmic solutions that expand testing coverage, improve problem-solving templates, and create reusable patterns for interview prep. With multi-test support, optimized DP approaches, and grid/backtracking techniques, the month established a solid foundation for scalable algorithm practice and future feature development. No major bugs fixed this month; development focused on feature delivery and correctness across tasks.
February 2025
8 Commits • 5 Features
Feb 1, 2025February 2025 monthly summary for UngSangYoon/Algorithm_Study_FISA: Focused on delivering Python tooling for algorithmic problems and improving repository hygiene to accelerate experimentation and collaboration. Implemented five features with clear, reusable scripts; no explicit bug fixes recorded this month; these changes collectively reduce time to prototype, improve data handling, and strengthen code hygiene for maintainability.
8 Commits • 5 Features
Feb 1, 2025February 2025 monthly summary for UngSangYoon/Algorithm_Study_FISA: Focused on delivering Python tooling for algorithmic problems and improving repository hygiene to accelerate experimentation and collaboration. Implemented five features with clear, reusable scripts; no explicit bug fixes recorded this month; these changes collectively reduce time to prototype, improve data handling, and strengthen code hygiene for maintainability.
February 2025
January 2025
4 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for UngSangYoon/Algorithm_Study_FISA focused on feature delivery and foundational tooling for algorithm practice.
January 2025
4 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for UngSangYoon/Algorithm_Study_FISA focused on feature delivery and foundational tooling for algorithm practice.
Activity
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Quality Metrics
Correctness96.4%
Maintainability91.4%
Architecture89.4%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
GitPython
Technical Skills
AlgorithmAlgorithm DesignAlgorithm ImplementationBacktrackingBitmaskingCombinatoricsData StructuresDepth-First SearchDepth-First Search (DFS)Dynamic ProgrammingGreedy AlgorithmGreedy AlgorithmsModular ArithmeticNumber TheoryPermutations
Repositories Contributed To
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