AlgoriGym-study/AlgoriGym
Feb 2025 – May 2025
4 Months active
Languages Used
JavatxtMarkdown
Technical Skills
AlgorithmBrute ForceData StructuresDepth First SearchDepth-First SearchFile I/O
Jayeun Park
PROFILE
Jayeun Park
Jayeun Pak developed a robust suite of algorithmic solutions for the AlgoriGym-study/AlgoriGym repository, focusing on grid-based pathfinding, dynamic programming, and string manipulation challenges. Over four months, Jayeun implemented features such as Dijkstra’s and BFS-driven solvers, binary search modules, and simulation tools for tasks like robot collision detection. The work emphasized clean Java code, reusable modules, and careful input handling, supporting both contest preparation and educational use. Jayeun’s approach included thoughtful code organization and refactoring, resulting in a maintainable codebase that accelerates onboarding and future enhancements while ensuring correctness across a diverse set of algorithmic problems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
46Total
Bugs
0
Commits
46
Features
14
Lines of code
5,672
Activity Months4
Your Network
12 people
Work History
May 2025
4 Commits • 3 Features
May 1, 2025May 2025 monthly summary for AlgoriGym: Delivered three algorithm-focused features that expand the learner-friendly challenge library while maintaining code quality and traceability. Implemented Binary Search Challenge Solvers for two problems (minimum skill level within a time limit; minimum time for immigration checks), a Brute-force Substring Search for SWEA, and a Robot Collision Detection simulator that tracks movements on a grid over time to identify potential collisions. No major bugs reported this month; commits provide clear references for future auditing and enhancements. The work demonstrates strong algorithmic implementation, Java proficiency for string searching, and time-based simulation techniques, contributing to improved learning outcomes and platform reliability.
4 Commits • 3 Features
May 1, 2025May 2025 monthly summary for AlgoriGym: Delivered three algorithm-focused features that expand the learner-friendly challenge library while maintaining code quality and traceability. Implemented Binary Search Challenge Solvers for two problems (minimum skill level within a time limit; minimum time for immigration checks), a Brute-force Substring Search for SWEA, and a Robot Collision Detection simulator that tracks movements on a grid over time to identify potential collisions. No major bugs reported this month; commits provide clear references for future auditing and enhancements. The work demonstrates strong algorithmic implementation, Java proficiency for string searching, and time-based simulation techniques, contributing to improved learning outcomes and platform reliability.
May 2025
April 2025
17 Commits • 2 Features
Apr 1, 2025Month: 2025-04. This period focused on delivering a reusable algorithmic toolkit and robust grid-based pathfinding capabilities across the AlgoriGym repository, with emphasis on practical business value and scalable implementation. Key features delivered - Grid-based Pathfinding and Traversal Algorithms: Implemented Dijkstra and BFS driven solutions across multiple problems (competitive infection, routing, delivery, fugitive chase, matrix processing, maze navigation). Core commits include: fb20b1c062643ac3c233b3a84a944f8c3e34772f, c62d826e0985f91d3a5c75719232d2c9c27a1455, 7c63c16601f6ee5fd8cebc87814b6a6b92378c6f, 4a20f4191d59958920d8b644b2f1965f2f88e2a1, bf762cbd761ea4148708dcc178b7b294039026f4, 10109b09c33161171b63ac4f7e97b17ed7498959, 39c8679f17cfcb323bf64b2bba04f3ea70228da5, 8e79e8c6d7398e669883c50c4a25762c915c4826, b729414d512949cbc01bef21785bdc79a2e3aa4c. - General Algorithmic Solutions (DP, BFS, Stacks, and more): Expanded problem-solving coverage to knapsack, visit length, stock price, Puyo Puyo, mode finding, high shelf, and a mixed problem in a single commit. Key commits include: d51df4027fcae734f057701d02da4e80a9a132b1, 1fdc3b1a6eca4dc8f11b3ab7d3e3699d4e2db2ea, 56e5206c07e88a1f7a3eabc6ad86bebdd3963512, 8379e15f5c0a12066d9018bb8280ebdeab6e1ae6, 6abf26532d2bc1addc1cd3b4625b6f8abd795b62, 1c8ce53aeb019486606dcd72bd5acf00382cb27b, 1c404514a3218b762bf182ba035c63ef001ee547, 124355950655326b1650e8d12c97bff55755a858. Major bugs fixed - No explicit bugfix tickets are documented in this period. Focused on feature delivery with stabilizing edge-case handling and input validation within pathfinding and DP modules to improve reliability across challenges. Some commits inherently refined existing solutions to ensure correctness across diverse test cases. Overall impact and accomplishments - Built a reusable, battle-tested algorithmic toolkit enabling rapid solution of a broad set of competitive programming problems (SWEA, Programmers, Baekjoon). This reduces cycle time for future challenge iterations and strengthens repository maintainability and knowledge transfer. - Demonstrated end-to-end delivery: from algorithm design (Dijkstra, BFS, DP) and implementation to validation across multiple problem domains, enhancing the team's capacity to address complex routing, grid-processing, and optimization tasks. Technologies/skills demonstrated - Grid algorithms: Dijkstra, BFS, traversal on grids, maze navigation. - Dynamic programming, BFS, stacks, and problem-solving across diverse domains (knapsack, visiting length, stock price, Puyo Puyo, mode finding, high shelf, etc.). - Platform-aware scripting and problem framing for SWEA, Programmers, and Baekjoon formats; emphasis on clean, reusable modules and clear commit history.
April 2025
17 Commits • 2 Features
Apr 1, 2025Month: 2025-04. This period focused on delivering a reusable algorithmic toolkit and robust grid-based pathfinding capabilities across the AlgoriGym repository, with emphasis on practical business value and scalable implementation. Key features delivered - Grid-based Pathfinding and Traversal Algorithms: Implemented Dijkstra and BFS driven solutions across multiple problems (competitive infection, routing, delivery, fugitive chase, matrix processing, maze navigation). Core commits include: fb20b1c062643ac3c233b3a84a944f8c3e34772f, c62d826e0985f91d3a5c75719232d2c9c27a1455, 7c63c16601f6ee5fd8cebc87814b6a6b92378c6f, 4a20f4191d59958920d8b644b2f1965f2f88e2a1, bf762cbd761ea4148708dcc178b7b294039026f4, 10109b09c33161171b63ac4f7e97b17ed7498959, 39c8679f17cfcb323bf64b2bba04f3ea70228da5, 8e79e8c6d7398e669883c50c4a25762c915c4826, b729414d512949cbc01bef21785bdc79a2e3aa4c. - General Algorithmic Solutions (DP, BFS, Stacks, and more): Expanded problem-solving coverage to knapsack, visit length, stock price, Puyo Puyo, mode finding, high shelf, and a mixed problem in a single commit. Key commits include: d51df4027fcae734f057701d02da4e80a9a132b1, 1fdc3b1a6eca4dc8f11b3ab7d3e3699d4e2db2ea, 56e5206c07e88a1f7a3eabc6ad86bebdd3963512, 8379e15f5c0a12066d9018bb8280ebdeab6e1ae6, 6abf26532d2bc1addc1cd3b4625b6f8abd795b62, 1c8ce53aeb019486606dcd72bd5acf00382cb27b, 1c404514a3218b762bf182ba035c63ef001ee547, 124355950655326b1650e8d12c97bff55755a858. Major bugs fixed - No explicit bugfix tickets are documented in this period. Focused on feature delivery with stabilizing edge-case handling and input validation within pathfinding and DP modules to improve reliability across challenges. Some commits inherently refined existing solutions to ensure correctness across diverse test cases. Overall impact and accomplishments - Built a reusable, battle-tested algorithmic toolkit enabling rapid solution of a broad set of competitive programming problems (SWEA, Programmers, Baekjoon). This reduces cycle time for future challenge iterations and strengthens repository maintainability and knowledge transfer. - Demonstrated end-to-end delivery: from algorithm design (Dijkstra, BFS, DP) and implementation to validation across multiple problem domains, enhancing the team's capacity to address complex routing, grid-processing, and optimization tasks. Technologies/skills demonstrated - Grid algorithms: Dijkstra, BFS, traversal on grids, maze navigation. - Dynamic programming, BFS, stacks, and problem-solving across diverse domains (knapsack, visiting length, stock price, Puyo Puyo, mode finding, high shelf, etc.). - Platform-aware scripting and problem framing for SWEA, Programmers, and Baekjoon formats; emphasis on clean, reusable modules and clear commit history.
March 2025
20 Commits • 4 Features
Mar 1, 2025March 2025 progress highlights include the delivery of a scalable algorithmic toolkit and a targeted codebase refactor to support maintainability and onboarding. Key initiatives expanded contest-prep capabilities, improved code organization, and demonstrated strong problem-solving and software design skills.
20 Commits • 4 Features
Mar 1, 2025March 2025 progress highlights include the delivery of a scalable algorithmic toolkit and a targeted codebase refactor to support maintainability and onboarding. Key initiatives expanded contest-prep capabilities, improved code organization, and demonstrated strong problem-solving and software design skills.
March 2025
February 2025
5 Commits • 5 Features
Feb 1, 2025February 2025 — AlgoriGym: Delivered multiple Java-based algorithm implementations across five problems, with a focus on correctness, input handling, and basic performance considerations. The work enhances the platform's problem-solving toolkit, enabling users to study and practice common algorithmic patterns more effectively. Key focus areas included trees, grids, and graph traversal, with clean commits and groundwork for future refactoring.
February 2025
5 Commits • 5 Features
Feb 1, 2025February 2025 — AlgoriGym: Delivered multiple Java-based algorithm implementations across five problems, with a focus on correctness, input handling, and basic performance considerations. The work enhances the platform's problem-solving toolkit, enabling users to study and practice common algorithmic patterns more effectively. Key focus areas included trees, grids, and graph traversal, with clean commits and groundwork for future refactoring.
Activity
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Quality Metrics
Correctness91.6%
Maintainability81.4%
Architecture77.4%
Performance80.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaMarkdowntxt
Technical Skills
AlgorithmAlgorithm ImplementationBack-end DevelopmentBacktrackingBinary SearchBreadth-First SearchBreadth-First Search (BFS)Brute ForceChessboard ProblemsCode OrganizationData StructuresDepth First SearchDepth First Search (DFS)Depth-First SearchDijkstra's Algorithm
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