AlgoriGym-study/AlgoriGym
Apr 2025 – Feb 2026
11 Months active
Languages Used
JavaMarkdownSQL
Technical Skills
AlgorithmBacktrackingDepth First SearchFile ManagementMaze SolvingProblem Solving
Jayeun Park
PROFILE
Jayeun Park
Jayeun Park developed a robust suite of algorithmic solutions and analytics features for the AlgoriGym-study/AlgoriGym repository, focusing on reusable problem-solving modules and data-driven utilities. Leveraging Java and SQL, Jayeun implemented features such as dynamic programming solvers, graph traversal toolkits, and advanced data analysis queries, addressing challenges in grid navigation, combinatorics, and reporting. The work included end-to-end systems like parking fee calculation, server scaling logic, and sequence transformation engines, all designed for maintainability and extensibility. Through disciplined code organization, clear documentation, and iterative refactoring, Jayeun ensured the codebase remained scalable, reliable, and ready for rapid onboarding and future enhancements.
Overall Statistics
Feature vs Bugs
98%Features
Repository Contributions
96Total
Bugs
1
Commits
96
Features
53
Lines of code
3,152
Activity Months11
Your Network
12 people
Work History
February 2026
2 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for AlgoriGym study (AlgoriGym). Focused on delivering core analytics capabilities and sequence transformation logic. Delivered two key features: Data Analysis: Advanced Filtering and Sorting, and Sequence Transformation Engine Improvement, with commits 2371e3d7aacaf4342299733c7a1b794ff2976772 and cf579779c0fcbc93669ad13f00c88a2192e511d7. No major bugs fixed this month. Overall impact: enhanced data prep, analytics readiness, and deterministic sequence processing, enabling faster problem solving and improved user workflows. Technologies/skills demonstrated: Python, algorithm design, data structures, problem solving, version-control discipline, and evidence-based development through commit history.
2 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for AlgoriGym study (AlgoriGym). Focused on delivering core analytics capabilities and sequence transformation logic. Delivered two key features: Data Analysis: Advanced Filtering and Sorting, and Sequence Transformation Engine Improvement, with commits 2371e3d7aacaf4342299733c7a1b794ff2976772 and cf579779c0fcbc93669ad13f00c88a2192e511d7. No major bugs fixed this month. Overall impact: enhanced data prep, analytics readiness, and deterministic sequence processing, enabling faster problem solving and improved user workflows. Technologies/skills demonstrated: Python, algorithm design, data structures, problem solving, version-control discipline, and evidence-based development through commit history.
February 2026
January 2026
20 Commits • 7 Features
Jan 1, 2026Concise monthly summary for 2026-01: Key features delivered: - Parking Fee Calculation System: end-to-end parking management—track vehicle entry/exit times, compute total duration, and calculate fees based on configurable rates. Representative commits: c640c94b7c112d89083730b6c87e145df9ccced5; c609a7864b7f5cff19fe1a243a71bf83682e24de. - SQL Data Analysis Queries: data-driven insights with queries for largest fish by length and classification of E. coli colony sizes. Representative commits: 52c4570399a71ba25f37f1a36fb1c86bfcadb2eb; 265f3171ce4cf94ba8eb5a231eb75b51e651a598. - Base-k Prime Counting Utilities: counting primes in base-k representations to support advanced number-theory exercises. Representative commits: cce9e010d23d3118abaa178827fbbdfa900308d1; df44cbacd75a1cdeb9fd03b2134096fa775e535b. - Server Scaling for Game Infrastructure: dynamic server scaling based on player demand with expiration tracking to maintain performance under peak loads. Commit: af80d9a9e6ce816bc9d37df0564fcbd87e314dd2. - Lottery Ranking Mechanism: compute highest and lowest lottery ranks based on matches and zeros, enabling faster win-rate analysis. Commit: 73e4240608c256c7857325e5870113439e45e4b0. Major bugs fixed: - No high-severity bugs reported; the month focused on feature delivery and systemic improvements. Stability and reliability were enhanced via server-scaling adjustments and maintainance work (e.g., file renames and refactors) to reduce technical debt. Overall impact and accomplishments: - Delivered end-to-end capabilities across pricing, analytics, and scalable infrastructure, enabling revenue accuracy, data-driven decision making, and scalable game services. These efforts position the platform for higher traffic, improved user experiences, and faster iteration cycles. Technologies/skills demonstrated: - System design and implementation of end-to-end features, SQL data analysis, number theory utilities, dynamic server scaling, and lottery ranking logic. - Proficiency in algorithm design, data processing, SQL, and performance considerations for scalable services. - Strong code hygiene through maintenance and refactoring activities.
January 2026
20 Commits • 7 Features
Jan 1, 2026Concise monthly summary for 2026-01: Key features delivered: - Parking Fee Calculation System: end-to-end parking management—track vehicle entry/exit times, compute total duration, and calculate fees based on configurable rates. Representative commits: c640c94b7c112d89083730b6c87e145df9ccced5; c609a7864b7f5cff19fe1a243a71bf83682e24de. - SQL Data Analysis Queries: data-driven insights with queries for largest fish by length and classification of E. coli colony sizes. Representative commits: 52c4570399a71ba25f37f1a36fb1c86bfcadb2eb; 265f3171ce4cf94ba8eb5a231eb75b51e651a598. - Base-k Prime Counting Utilities: counting primes in base-k representations to support advanced number-theory exercises. Representative commits: cce9e010d23d3118abaa178827fbbdfa900308d1; df44cbacd75a1cdeb9fd03b2134096fa775e535b. - Server Scaling for Game Infrastructure: dynamic server scaling based on player demand with expiration tracking to maintain performance under peak loads. Commit: af80d9a9e6ce816bc9d37df0564fcbd87e314dd2. - Lottery Ranking Mechanism: compute highest and lowest lottery ranks based on matches and zeros, enabling faster win-rate analysis. Commit: 73e4240608c256c7857325e5870113439e45e4b0. Major bugs fixed: - No high-severity bugs reported; the month focused on feature delivery and systemic improvements. Stability and reliability were enhanced via server-scaling adjustments and maintainance work (e.g., file renames and refactors) to reduce technical debt. Overall impact and accomplishments: - Delivered end-to-end capabilities across pricing, analytics, and scalable infrastructure, enabling revenue accuracy, data-driven decision making, and scalable game services. These efforts position the platform for higher traffic, improved user experiences, and faster iteration cycles. Technologies/skills demonstrated: - System design and implementation of end-to-end features, SQL data analysis, number theory utilities, dynamic server scaling, and lottery ranking logic. - Proficiency in algorithm design, data processing, SQL, and performance considerations for scalable services. - Strong code hygiene through maintenance and refactoring activities.
December 2025
17 Commits • 2 Features
Dec 1, 2025December 2025 — Delivered cross-domain analytics enhancements and a new string/algorithm utilities suite for AlgoriGym, delivering business value through richer reporting, more robust data retrieval, and enhanced internal tooling. Focused on feature delivery, tooling improvements, and laying groundwork for data-driven decision making.
17 Commits • 2 Features
Dec 1, 2025December 2025 — Delivered cross-domain analytics enhancements and a new string/algorithm utilities suite for AlgoriGym, delivering business value through richer reporting, more robust data retrieval, and enhanced internal tooling. Focused on feature delivery, tooling improvements, and laying groundwork for data-driven decision making.
December 2025
November 2025
5 Commits • 3 Features
Nov 1, 2025November 2025 monthly summary — AlgoriGym study repository
November 2025
5 Commits • 3 Features
Nov 1, 2025November 2025 monthly summary — AlgoriGym study repository
October 2025
14 Commits • 12 Features
Oct 1, 2025October 2025 monthly summary for AlgoriGym – Focused on delivering high-value algorithmic solutions, improving code maintainability, and enabling faster onboarding through clear commits and documentation alignment.
14 Commits • 12 Features
Oct 1, 2025October 2025 monthly summary for AlgoriGym – Focused on delivering high-value algorithmic solutions, improving code maintainability, and enabling faster onboarding through clear commits and documentation alignment.
October 2025
September 2025
11 Commits • 8 Features
Sep 1, 2025Summary for 2025-09: Delivered a cohesive set of algorithm-focused features in AlgoriGym, strengthening the reusable problem-solving library and accelerating learning and prototyping for the team. Key features delivered include a suite of Java solutions for Baekjoon-style problems and related grid/pathfinding tasks, with attention to clarity and reuse. Major bugs fixed and stability improvements were applied where noted, enhancing reliability for ongoing development. Key features delivered: - Recursive Function Problem Solution: Java solution for Baekjoon 'What is a Recursive Function?' using a recursive storytelling approach with depth-indentation. Commit 2506d707aaea941af3d1a06ceeb6226f5d61dc92 - Graph Traversal Toolkit (DFS & BFS) and Alphabet Problem: Java DFS/BFS toolkit; includes a DFS solution for Baekjoon Alphabet problem. Commits 30b8615c048e2f610670330283e510ef75c87de9 and 931d511afdca3a5a91bb1cfe2c11298d35a56bc6 - Break the Wall and Move – BFS Pathfinding with One Wall Break: BFS-based grid navigation with one wall destruction. Commit ab294d9a1f30a79d2e5140835a0bb08043280a35 - Hide and Seek – Shortest Time via BFS: BFS solution to reach target with moves including teleport; Baekjoon 'Hide and Seek'. Commit d68394bb30e1da4a3fa18e4da82031cddfc5a6a8 - Collatz Conjecture Solver with Safety Cap: Java solution to compute steps to reach 1 under Collatz rules with a safeguard cap; includes a fix adjusting the cap logic. Commits f24b5cdbb0b000f8e45bff15b42bf0f1ce553430 and ce0f1c027f220897b0a0f9b97e5b8d0b1e6daf33 - Park Walk – Grid Navigation with Routes: Java solution simulating movement on a park grid according to given routes; handles boundaries and obstacles. Commits 2d8d249ac76fdacdfac9b3803fc15b7c871876ec and 76082c0efa77b5ebde3ef1acf040393d77d33fbf - Jewel Thief – Greedy Jewels on Bags: Greedy algorithm using a priority queue to maximize jewel value given bag capacities. Commit 12af44672ac9c55595947b68c878216c0d653b88 - Park – Largest Square Mat in Parking Grid: Algorithm to check for the largest square mat that fits into a park grid using a 2D prefix sum; handles occupied spots. Commit bd7fedd8efda068ec4ca5e02dfafdae6afb1017c Major improvements and impact: - Strengthened problem-solving library with eight concrete Java implementations that are reusable for interviews, training, and onboarding. - Improved reliability through targeted fixes (notably the Collatz cap logic) and enhanced boundary/obstacle handling in grid-based problems. - Delivered end-to-end solutions from problem statement to testable Java code, enabling faster knowledge transfer and hands-on practice for the team. Technologies/skills demonstrated: - Java, object-oriented design, and clean coding practices - Graph algorithms: DFS, BFS, and graph traversal patterns - Grid-based pathfinding and routing, including one-wall break scenarios - Data structures: priority queues, 2D arrays, and 2D prefix sums - Defensive programming and safety checks for termination conditions - Clear commit traceability for each feature
September 2025
11 Commits • 8 Features
Sep 1, 2025Summary for 2025-09: Delivered a cohesive set of algorithm-focused features in AlgoriGym, strengthening the reusable problem-solving library and accelerating learning and prototyping for the team. Key features delivered include a suite of Java solutions for Baekjoon-style problems and related grid/pathfinding tasks, with attention to clarity and reuse. Major bugs fixed and stability improvements were applied where noted, enhancing reliability for ongoing development. Key features delivered: - Recursive Function Problem Solution: Java solution for Baekjoon 'What is a Recursive Function?' using a recursive storytelling approach with depth-indentation. Commit 2506d707aaea941af3d1a06ceeb6226f5d61dc92 - Graph Traversal Toolkit (DFS & BFS) and Alphabet Problem: Java DFS/BFS toolkit; includes a DFS solution for Baekjoon Alphabet problem. Commits 30b8615c048e2f610670330283e510ef75c87de9 and 931d511afdca3a5a91bb1cfe2c11298d35a56bc6 - Break the Wall and Move – BFS Pathfinding with One Wall Break: BFS-based grid navigation with one wall destruction. Commit ab294d9a1f30a79d2e5140835a0bb08043280a35 - Hide and Seek – Shortest Time via BFS: BFS solution to reach target with moves including teleport; Baekjoon 'Hide and Seek'. Commit d68394bb30e1da4a3fa18e4da82031cddfc5a6a8 - Collatz Conjecture Solver with Safety Cap: Java solution to compute steps to reach 1 under Collatz rules with a safeguard cap; includes a fix adjusting the cap logic. Commits f24b5cdbb0b000f8e45bff15b42bf0f1ce553430 and ce0f1c027f220897b0a0f9b97e5b8d0b1e6daf33 - Park Walk – Grid Navigation with Routes: Java solution simulating movement on a park grid according to given routes; handles boundaries and obstacles. Commits 2d8d249ac76fdacdfac9b3803fc15b7c871876ec and 76082c0efa77b5ebde3ef1acf040393d77d33fbf - Jewel Thief – Greedy Jewels on Bags: Greedy algorithm using a priority queue to maximize jewel value given bag capacities. Commit 12af44672ac9c55595947b68c878216c0d653b88 - Park – Largest Square Mat in Parking Grid: Algorithm to check for the largest square mat that fits into a park grid using a 2D prefix sum; handles occupied spots. Commit bd7fedd8efda068ec4ca5e02dfafdae6afb1017c Major improvements and impact: - Strengthened problem-solving library with eight concrete Java implementations that are reusable for interviews, training, and onboarding. - Improved reliability through targeted fixes (notably the Collatz cap logic) and enhanced boundary/obstacle handling in grid-based problems. - Delivered end-to-end solutions from problem statement to testable Java code, enabling faster knowledge transfer and hands-on practice for the team. Technologies/skills demonstrated: - Java, object-oriented design, and clean coding practices - Graph algorithms: DFS, BFS, and graph traversal patterns - Grid-based pathfinding and routing, including one-wall break scenarios - Data structures: priority queues, 2D arrays, and 2D prefix sums - Defensive programming and safety checks for termination conditions - Clear commit traceability for each feature
August 2025
6 Commits • 4 Features
Aug 1, 2025August 2025 monthly summary for AlgoriGym-study/AlgoriGym. Delivered four core features/optimizations across greedy digit removal, tetromino max-sum, and sensor placement, plus extensive codebase restructuring. These efforts improved solution accuracy, runtime efficiency, and maintainability, directly contributing to business value and a future-ready codebase.
6 Commits • 4 Features
Aug 1, 2025August 2025 monthly summary for AlgoriGym-study/AlgoriGym. Delivered four core features/optimizations across greedy digit removal, tetromino max-sum, and sensor placement, plus extensive codebase restructuring. These efforts improved solution accuracy, runtime efficiency, and maintainability, directly contributing to business value and a future-ready codebase.
August 2025
July 2025
13 Commits • 8 Features
Jul 1, 2025July 2025 performance highlights for AlgoriGym: Delivered a set of feature-ready algorithmic improvements across the repository, emphasizing data privacy, dynamic programming, and efficient data-structure solutions. No explicit critical bug fixes were recorded in this period; the focus was on delivering high-value features, improving computations, and strengthening maintainability through documentation. Business impact includes stronger privacy policy enforcement with expiration-aware data handling, faster DP-based computation paths, and scalable data operations. Technologies demonstrated include Java, dynamic programming, DSU, median maintenance with priority queues, sorting, and documentation practices.
July 2025
13 Commits • 8 Features
Jul 1, 2025July 2025 performance highlights for AlgoriGym: Delivered a set of feature-ready algorithmic improvements across the repository, emphasizing data privacy, dynamic programming, and efficient data-structure solutions. No explicit critical bug fixes were recorded in this period; the focus was on delivering high-value features, improving computations, and strengthening maintainability through documentation. Business impact includes stronger privacy policy enforcement with expiration-aware data handling, faster DP-based computation paths, and scalable data operations. Technologies demonstrated include Java, dynamic programming, DSU, median maintenance with priority queues, sorting, and documentation practices.
June 2025
3 Commits • 3 Features
Jun 1, 2025June 2025 performance highlights for AlgoriGym-study/AlgoriGym: Delivered core algorithm features, improved code organization, and implemented a data-driven optimization experiment, contributing to product readiness and scalable maintenance. No critical defects identified; minor packaging cleanups and code quality improvements reduced future maintenance overhead.
3 Commits • 3 Features
Jun 1, 2025June 2025 performance highlights for AlgoriGym-study/AlgoriGym: Delivered core algorithm features, improved code organization, and implemented a data-driven optimization experiment, contributing to product readiness and scalable maintenance. No critical defects identified; minor packaging cleanups and code quality improvements reduced future maintenance overhead.
June 2025
May 2025
2 Commits • 2 Features
May 1, 2025May 2025 monthly summary for AlgoriGym-study/AlgoriGym. Delivered two core algorithmic features with clear outcomes: a stack-based Parentheses Matching Validator and a Warehouse Cleaning problem solver. No explicit critical bugs reported; focus was on correctness, maintainability, and expanding solution coverage in the repository.
May 2025
2 Commits • 2 Features
May 1, 2025May 2025 monthly summary for AlgoriGym-study/AlgoriGym. Delivered two core algorithmic features with clear outcomes: a stack-based Parentheses Matching Validator and a Warehouse Cleaning problem solver. No explicit critical bugs reported; focus was on correctness, maintainability, and expanding solution coverage in the repository.
April 2025
3 Commits • 2 Features
Apr 1, 2025Apr 2025 monthly summary for AlgoriGym-study/AlgoriGym focusing on feature delivery, impact, and technical leadership. Delivered two core algorithmic solvers expanding the project’s problem-solving toolkit: the Maze Escape Command Solver (DFS-based, finds the lexicographically smallest path to escape a maze within a step limit, with pruning to eliminate infeasible branches) and the Water Shortage Problem Solver (forecasts daily water usage to identify the first day storage capacity is exceeded, returning -1 if never exceeded). Implemented accompanying code hygiene improvements and small refactors to improve maintainability. These efforts reduce time-to-solution for common challenge patterns and provide a solid foundation for further optimization and benchmarking. Commits tied to these features include 39a6e44f6472a64d32d494ea4d2d76ca6da12a93 and b320273a886c93108d482906e3c9e3df008a86c1 for the Maze feature, and 62a3b1c12cbd29728578d06be525faaa3db2f0f2 for the Water Shortage solver.
3 Commits • 2 Features
Apr 1, 2025Apr 2025 monthly summary for AlgoriGym-study/AlgoriGym focusing on feature delivery, impact, and technical leadership. Delivered two core algorithmic solvers expanding the project’s problem-solving toolkit: the Maze Escape Command Solver (DFS-based, finds the lexicographically smallest path to escape a maze within a step limit, with pruning to eliminate infeasible branches) and the Water Shortage Problem Solver (forecasts daily water usage to identify the first day storage capacity is exceeded, returning -1 if never exceeded). Implemented accompanying code hygiene improvements and small refactors to improve maintainability. These efforts reduce time-to-solution for common challenge patterns and provide a solid foundation for further optimization and benchmarking. Commits tied to these features include 39a6e44f6472a64d32d494ea4d2d76ca6da12a93 and b320273a886c93108d482906e3c9e3df008a86c1 for the Maze feature, and 62a3b1c12cbd29728578d06be525faaa3db2f0f2 for the Water Shortage solver.
April 2025
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Quality Metrics
Correctness96.2%
Maintainability91.4%
Architecture90.4%
Performance90.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaMarkdownSQL
Technical Skills
AlgorithmAlgorithm AnalysisAlgorithm ImplementationAlgorithm Problem SolvingAlgorithm StudyBFSBacktrackingBreadth-First SearchCode OrganizationCombinatoricsDFSData StructuresDatabaseDatabase QueryingDepth First Search
Repositories Contributed To
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