AlgoriGym-study/AlgoriGym
Jun 2025 – Oct 2025
5 Months active
Languages Used
JavaMarkdown
Technical Skills
AlgorithmAlgorithm DesignAlgorithmsBacktrackingData StructuresDijkstra's Algorithm
mirim
PROFILE
Mirim
Developed and maintained a comprehensive algorithmic solutions library in the AlgoriGym-study/AlgoriGym repository over five months, delivering twenty features and addressing a range of competitive programming challenges. Built Java-based modules for dynamic programming, graph traversal, greedy optimization, and grid-based simulations, including implementations such as Snake Game Simulation, Baby Shark grid navigation, and Dijkstra’s pathfinding. Applied techniques like depth-first search, priority queues, and sliding window algorithms to solve real-world and contest problems. Enhanced code quality through modular design, documentation, and refactoring, supporting maintainability and onboarding. Demonstrated expertise in Java, data structures, and algorithm design, with a focus on reusable, testable solutions.
Overall Statistics
Feature vs Bugs
91%Features
Repository Contributions
34Total
Bugs
2
Commits
34
Features
20
Lines of code
2,413
Activity Months5
Your Network
14 peopleShared Repositories
14
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Work History
October 2025
2 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for AlgoriGym: Delivered two Java-based algorithmic solutions expanding the repository’s competitive programming capabilities. Key features delivered include a DFS-based DP solution for Baekjoon 1005 ACM Craft to compute the minimum construction time by modeling dependencies as a graph and identifying the critical path, and a sorting-based greedy solution for Baekjoon 1202 Jewelry Thief to maximize value carried via a priority-queue approach. No major bugs reported this month; focus was on robust implementation, code quality, and maintainability. The work enhances problem-solving coverage, provides reusable algorithm patterns, and supports faster onboarding for similar tasks. Technologies demonstrated include Java, graph modeling, DFS-based dynamic programming, sorting, and priority queue-driven greedy algorithms. These contributions deliver business value by enabling faster, reliable solutions for optimization problems and strengthening the codebase for future extensions.
2 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for AlgoriGym: Delivered two Java-based algorithmic solutions expanding the repository’s competitive programming capabilities. Key features delivered include a DFS-based DP solution for Baekjoon 1005 ACM Craft to compute the minimum construction time by modeling dependencies as a graph and identifying the critical path, and a sorting-based greedy solution for Baekjoon 1202 Jewelry Thief to maximize value carried via a priority-queue approach. No major bugs reported this month; focus was on robust implementation, code quality, and maintainability. The work enhances problem-solving coverage, provides reusable algorithm patterns, and supports faster onboarding for similar tasks. Technologies demonstrated include Java, graph modeling, DFS-based dynamic programming, sorting, and priority queue-driven greedy algorithms. These contributions deliver business value by enabling faster, reliable solutions for optimization problems and strengthening the codebase for future extensions.
October 2025
September 2025
16 Commits • 13 Features
Sep 1, 20252025-09 Monthly Summary — AlgoriGym-study/AlgoriGym Key focus: deliver end-to-end algorithmic capabilities, improve code quality, and document complex problems to accelerate onboarding and future contribution. The month combined feature implementations, graph/DSP planning, grid-based simulations, and thorough documentation, with an emphasis on reliable, reusable components and measurable business value. Key features delivered - Baby Shark grid simulation (shark growth and movement): grid navigation, edible fish consumption, growth logic, and total time calculation. Commit: 7a22e5cf9727cb6dfdf65401ebb8033646baeee5. - Dijkstra pathfinding for Green-Clad Kid problem (Baekjoon 4485): minimum cost path on a grid supporting multiple test cases until input 0. Commit: ebb3910a61593f79f7b2fb11433ffccd7097e1df. - Largest number after removing digits (sliding window): generate the largest possible number by selecting digits within a sliding window while removing k digits. Commit: 48a3f17359faa250d7eb997de7faa284366f351f. - Snake game simulation with turns: grid-based apples, growth, turns, and termination conditions. Commit: b744715bd17836e89e921eab4ac23b6d41cbe934. - Break Down Walls and Move documentation: Markdown documentation detailing input/output formats and examples for the Break Down Walls algorithm. Commit: 59600dbfaee9c79f6a12401d50fc1d4133d2893d. - DFS for maximum unique alphabets (initial and enhanced): exploring grid to maximize unique alphabets with backtracking. Commits: 0277ec4ed63d46455dc1ba0eccccc3c3624d937c; 885fbd4061416af0417da3489375095dc58d96b5; ca9bba84d85db9f8c2ee268cb2aee2c3057cfb31. - ACM Craft (DP and DFS) — dynamic programming with dependencies to minimize construction time. Commit: 31b363b25634c51c65cb7e0ade206df634015ce9. - Sugar Delivery (BOJ 2839) — DP-based minimization of bags for a given weight. Commit: 7c7e4886e9fef953885303265dc8739cf4a59db8. - 1,2,3 Add DP solution (BOJ 9095) — counting ways to sum to N. Commit: 66f4614146c1ea51c39a24fcb20566696665c7b7. - 2xN tiling DP solution (BOJ 11726) — DP approach for tiling. Commit: d1a14b261b43eedf052e62f4e9a8a570c110b301. - KMR0045_2 — binary search for time gap to minimize processing time within constraints. Commit: cabcbbc8a34392fe4657cc09e07147c9fb059b94. - KMR0045.java — added explanatory comments to clarify tricky logic for readability. Commit: fb3daf33aff57a03a619907aa13c816f2ba63b41. - Break Down Walls and Move — additional documentation and problem breakdown associated with problem-solving library expansion. Major bugs fixed - Removed all existing code from KMR0044.java to reset the file and avoid broken references. Commit: bd5a7eabff325dbea72a9d730043d3b0ac7c1745. - Cleanup of blank lines in KMR0040_2 and KMR0044 to remove non-functional whitespace and improve readability. Commit: 9a727faae28aa8f7833a4c9a4f12fdc05f097c29. Overall impact and accomplishments - Expanded a versatile algorithm library across DFS, DP, graph algorithms, and grid-based simulations, enabling faster solution framing for competitive problems and real-world grid problems. - Improved code quality, readability, and maintainability through targeted refactors, comments, and documentation, reducing onboarding time for new contributors. - Delivered end-to-end problem-solving artifacts, including working implementations, testable code paths, and markdown docs that clarify input/output formats and edge cases for future reuse. - Demonstrated end-to-end development discipline: feature work, bug remediation, code cleanup, and documentation within a single monthly cycle. Technologies, skills demonstrated - Java-based implementations with algorithmic patterns: DFS (with backtracking), DP (multi-problem patterns), Dijkstra’s algorithm, sliding window techniques, and grid simulations. - Problem decomposition, incremental delivery, and code documentation practices (markdown docs and inline comments). - Emphasis on maintainability, scalability, and reuse for a growing problem-solving library.
September 2025
16 Commits • 13 Features
Sep 1, 20252025-09 Monthly Summary — AlgoriGym-study/AlgoriGym Key focus: deliver end-to-end algorithmic capabilities, improve code quality, and document complex problems to accelerate onboarding and future contribution. The month combined feature implementations, graph/DSP planning, grid-based simulations, and thorough documentation, with an emphasis on reliable, reusable components and measurable business value. Key features delivered - Baby Shark grid simulation (shark growth and movement): grid navigation, edible fish consumption, growth logic, and total time calculation. Commit: 7a22e5cf9727cb6dfdf65401ebb8033646baeee5. - Dijkstra pathfinding for Green-Clad Kid problem (Baekjoon 4485): minimum cost path on a grid supporting multiple test cases until input 0. Commit: ebb3910a61593f79f7b2fb11433ffccd7097e1df. - Largest number after removing digits (sliding window): generate the largest possible number by selecting digits within a sliding window while removing k digits. Commit: 48a3f17359faa250d7eb997de7faa284366f351f. - Snake game simulation with turns: grid-based apples, growth, turns, and termination conditions. Commit: b744715bd17836e89e921eab4ac23b6d41cbe934. - Break Down Walls and Move documentation: Markdown documentation detailing input/output formats and examples for the Break Down Walls algorithm. Commit: 59600dbfaee9c79f6a12401d50fc1d4133d2893d. - DFS for maximum unique alphabets (initial and enhanced): exploring grid to maximize unique alphabets with backtracking. Commits: 0277ec4ed63d46455dc1ba0eccccc3c3624d937c; 885fbd4061416af0417da3489375095dc58d96b5; ca9bba84d85db9f8c2ee268cb2aee2c3057cfb31. - ACM Craft (DP and DFS) — dynamic programming with dependencies to minimize construction time. Commit: 31b363b25634c51c65cb7e0ade206df634015ce9. - Sugar Delivery (BOJ 2839) — DP-based minimization of bags for a given weight. Commit: 7c7e4886e9fef953885303265dc8739cf4a59db8. - 1,2,3 Add DP solution (BOJ 9095) — counting ways to sum to N. Commit: 66f4614146c1ea51c39a24fcb20566696665c7b7. - 2xN tiling DP solution (BOJ 11726) — DP approach for tiling. Commit: d1a14b261b43eedf052e62f4e9a8a570c110b301. - KMR0045_2 — binary search for time gap to minimize processing time within constraints. Commit: cabcbbc8a34392fe4657cc09e07147c9fb059b94. - KMR0045.java — added explanatory comments to clarify tricky logic for readability. Commit: fb3daf33aff57a03a619907aa13c816f2ba63b41. - Break Down Walls and Move — additional documentation and problem breakdown associated with problem-solving library expansion. Major bugs fixed - Removed all existing code from KMR0044.java to reset the file and avoid broken references. Commit: bd5a7eabff325dbea72a9d730043d3b0ac7c1745. - Cleanup of blank lines in KMR0040_2 and KMR0044 to remove non-functional whitespace and improve readability. Commit: 9a727faae28aa8f7833a4c9a4f12fdc05f097c29. Overall impact and accomplishments - Expanded a versatile algorithm library across DFS, DP, graph algorithms, and grid-based simulations, enabling faster solution framing for competitive problems and real-world grid problems. - Improved code quality, readability, and maintainability through targeted refactors, comments, and documentation, reducing onboarding time for new contributors. - Delivered end-to-end problem-solving artifacts, including working implementations, testable code paths, and markdown docs that clarify input/output formats and edge cases for future reuse. - Demonstrated end-to-end development discipline: feature work, bug remediation, code cleanup, and documentation within a single monthly cycle. Technologies, skills demonstrated - Java-based implementations with algorithmic patterns: DFS (with backtracking), DP (multi-problem patterns), Dijkstra’s algorithm, sliding window techniques, and grid simulations. - Problem decomposition, incremental delivery, and code documentation practices (markdown docs and inline comments). - Emphasis on maintainability, scalability, and reuse for a growing problem-solving library.
August 2025
2 Commits • 1 Features
Aug 1, 2025Monthly Summary for 2025-08: Delivered a fully functional Snake Game Simulation feature for AlgoriGym on an N x N grid, including apples, snake movement, boundary checks, and self-collision. The feature is configurable via user input for board size, number of apples, and turn directions, enabling flexible experimentation and validation of core mechanics. Commits documenting the work: 457e250fc86db594c20a77d5faa2c38fede64cff and 87be3bad8ba50a9fffc43c35f23f6e9d44ef6429. No major bugs fixed this month. Overall impact is an interactive, educational module that demonstrates grid-based state management, input handling, and collision logic, with clear path for future enhancements (scoring, AI, multi-snake scenarios). Technologies/skills demonstrated: grid-based state management, boundary handling, collision detection, and incremental, traceable commits.
2 Commits • 1 Features
Aug 1, 2025Monthly Summary for 2025-08: Delivered a fully functional Snake Game Simulation feature for AlgoriGym on an N x N grid, including apples, snake movement, boundary checks, and self-collision. The feature is configurable via user input for board size, number of apples, and turn directions, enabling flexible experimentation and validation of core mechanics. Commits documenting the work: 457e250fc86db594c20a77d5faa2c38fede64cff and 87be3bad8ba50a9fffc43c35f23f6e9d44ef6429. No major bugs fixed this month. Overall impact is an interactive, educational module that demonstrates grid-based state management, input handling, and collision logic, with clear path for future enhancements (scoring, AI, multi-snake scenarios). Technologies/skills demonstrated: grid-based state management, boundary handling, collision detection, and incremental, traceable commits.
August 2025
July 2025
10 Commits • 1 Features
Jul 1, 2025July 2025 monthly performance summary for AlgoriGym-study/AlgoriGym. Focused on feature delivery and codebase maturation to enable faster prototyping of algorithmic challenges and maintainable growth. No high-severity bugs reported this month; primary efforts centered on feature consolidation, refactoring, and knowledge consolidation to improve reuse and onboarding.
July 2025
10 Commits • 1 Features
Jul 1, 2025July 2025 monthly performance summary for AlgoriGym-study/AlgoriGym. Focused on feature delivery and codebase maturation to enable faster prototyping of algorithmic challenges and maintainable growth. No high-severity bugs reported this month; primary efforts centered on feature consolidation, refactoring, and knowledge consolidation to improve reuse and onboarding.
June 2025
4 Commits • 3 Features
Jun 1, 2025June 2025 monthly highlights for AlgoriGym study repository. Key features delivered across KMR algorithm study: three new problem solutions (KMR0026, KMR0027, KMR0029) covering linked-list manipulation, Dijkstra-based Hide and Seek, and a dynamic programming approach to maximize expression value; a recursive solution for a secret code decryption problem; and an emoticon discount rate optimization solution to maximize user sign-ups and total sales. All work is tracked in AlgoriGym-study/AlgoriGym with clear commit history for traceability.
4 Commits • 3 Features
Jun 1, 2025June 2025 monthly highlights for AlgoriGym study repository. Key features delivered across KMR algorithm study: three new problem solutions (KMR0026, KMR0027, KMR0029) covering linked-list manipulation, Dijkstra-based Hide and Seek, and a dynamic programming approach to maximize expression value; a recursive solution for a secret code decryption problem; and an emoticon discount rate optimization solution to maximize user sign-ups and total sales. All work is tracked in AlgoriGym-study/AlgoriGym with clear commit history for traceability.
June 2025
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Quality Metrics
Correctness90.2%
Maintainability83.0%
Architecture81.2%
Performance81.2%
AI Usage20.6%
Skills & Technologies
Programming Languages
JavaMarkdown
Technical Skills
AlgorithmAlgorithm AnalysisAlgorithm DesignAlgorithm ImplementationAlgorithm StudyAlgorithmsBacktrackingBinary SearchBreadth-First Search (BFS)Code CleanupCode DocumentationCombinatoricsCompetitive ProgrammingData StructuresDepth First Search
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