Algumithm/study
Mar 2025 – Jul 2025
3 Months active
Languages Used
JavaMarkdown
Technical Skills
2D ArraysAlgorithmAlgorithm ImplementationAlgorithmsBack-end DevelopmentBacktracking
ZeppIine
PROFILE
Zeppiine
Min Kim developed a robust suite of algorithmic solutions in the Algumithm/study repository, focusing on pathfinding, graph connectivity, optimization, and scheduling challenges. Over three months, Min implemented features such as maze exploration, dynamic programming for resource allocation, and graph traversal algorithms using Java and advanced data structures. The work emphasized clean code organization, reusable patterns, and scalable approaches to problem solving, particularly for Baekjoon problem sets. By integrating techniques like breadth-first search, greedy algorithms, and priority queues, Min enabled automated evaluation and knowledge transfer, delivering a deep, well-structured library that supports both interview preparation and team learning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
40Total
Bugs
0
Commits
40
Features
26
Lines of code
2,053
Activity Months3
Your Network
5 peopleShared Repositories
5
Work History
July 2025
7 Commits • 7 Features
Jul 1, 2025July 2025 performance summary for Algumithm/study: Delivered 7 Java-based algorithmic features focused on capacity planning, route optimization, and dynamic programming, with robust implementations and clear commit history. The work spans server expansion planning, vehicle route camera coverage, circular house robber DP, box retrieval access analysis, budgeting DP, Tower of Hanoi, and multi-source BFS for shortest paths. These contributions translate to tangible business value in capacity forecasting, optimized security coverage, improved resource retrieval, cost-aware planning, and efficient graph-based computations.
7 Commits • 7 Features
Jul 1, 2025July 2025 performance summary for Algumithm/study: Delivered 7 Java-based algorithmic features focused on capacity planning, route optimization, and dynamic programming, with robust implementations and clear commit history. The work spans server expansion planning, vehicle route camera coverage, circular house robber DP, box retrieval access analysis, budgeting DP, Tower of Hanoi, and multi-source BFS for shortest paths. These contributions translate to tangible business value in capacity forecasting, optimized security coverage, improved resource retrieval, cost-aware planning, and efficient graph-based computations.
July 2025
April 2025
8 Commits • 8 Features
Apr 1, 2025April 2025 monthly summary for Algumithm/study: Delivered a cohesive set of eight Baekjoon algorithm solutions, expanding the repository with interview-ready implementations across multiple problem types and data structures. The work emphasizes scalable patterns, clean interfaces, and reusability to accelerate evaluation and learning. Business value is demonstrated through a strengthened problem-solving library reusable for candidate assessments and team knowledge transfer, enabling faster interview preparation and more consistent coding quality.
April 2025
8 Commits • 8 Features
Apr 1, 2025April 2025 monthly summary for Algumithm/study: Delivered a cohesive set of eight Baekjoon algorithm solutions, expanding the repository with interview-ready implementations across multiple problem types and data structures. The work emphasizes scalable patterns, clean interfaces, and reusability to accelerate evaluation and learning. Business value is demonstrated through a strengthened problem-solving library reusable for candidate assessments and team knowledge transfer, enabling faster interview preparation and more consistent coding quality.
March 2025
25 Commits • 11 Features
Mar 1, 2025March 2025 — Algumithm/study: Delivered a diversified suite of algorithmic features and batch problem solutions, expanding core capabilities in pathfinding, graph connectivity, encoding/virus problems, optimization, scheduling, and problem-solving workflows. Implemented and integrated end-to-end solutions across multiple Baekjoon problems (Mar_2 batch) and Runway Construction (Mar_3), guided by weekly goals. Focused on business value by enabling automated problem solving, experimentation with optimization strategies, and scalable scheduling patterns. No explicit bug fixes were listed in the provided data; stability improvements were achieved as part of iterative feature development.
25 Commits • 11 Features
Mar 1, 2025March 2025 — Algumithm/study: Delivered a diversified suite of algorithmic features and batch problem solutions, expanding core capabilities in pathfinding, graph connectivity, encoding/virus problems, optimization, scheduling, and problem-solving workflows. Implemented and integrated end-to-end solutions across multiple Baekjoon problems (Mar_2 batch) and Runway Construction (Mar_3), guided by weekly goals. Focused on business value by enabling automated problem solving, experimentation with optimization strategies, and scalable scheduling patterns. No explicit bug fixes were listed in the provided data; stability improvements were achieved as part of iterative feature development.
March 2025
Activity
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Quality Metrics
Correctness92.6%
Maintainability87.6%
Architecture85.0%
Performance85.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaMarkdown
Technical Skills
2D ArraysAlgorithmAlgorithm DesignAlgorithm ImplementationAlgorithmsBack-end DevelopmentBacktrackingBinary SearchBreadth-First Search (BFS)Code OrganizationCompetitive ProgrammingData StructuresData structuresDepth First SearchDepth-First Search
Repositories Contributed To
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