leejihoindaeyo/Uwith_DataStructure
Nov 2024 – Dec 2024
2 Months active
Languages Used
MarkdownPython
Technical Skills
AlgorithmAlgorithm AnalysisAlgorithm ImplementationAlgorithmic ThinkingAlgorithmsBFS
최성민
PROFILE
최성민
Over two months, Lee Jihoin developed a robust algorithm toolkit within the leejihoindaeyo/Uwith_DataStructure repository, focusing on reusable Python modules for substring analysis, graph and tree traversal, and allocation problems. Lee implemented solutions such as sorting-based crane and box assignment and binary search-driven budget allocation, emphasizing edge-case handling and maintainability. The work included building foundational data structures, traversal utilities, and clear documentation to support onboarding and code review. In December, Lee established project scaffolding for future data structure modules, ensuring a scalable architecture. The engineering demonstrated depth in algorithmic thinking, data structure implementation, and collaborative documentation practices using Python and Markdown.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
21Total
Bugs
0
Commits
21
Features
7
Lines of code
526
Activity Months2
Your Network
10 people
Work History
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary focused on establishing foundational infrastructure for the Data Structure module in the Uwith_DataStructure project. Delivered scaffolding for Group3 Sungmin within WeighedGraph with placeholder files and a clear project layout. No functional changes were deployed this month, but the groundwork accelerates upcoming implementation and future feature delivery.
3 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary focused on establishing foundational infrastructure for the Data Structure module in the Uwith_DataStructure project. Delivered scaffolding for Group3 Sungmin within WeighedGraph with placeholder files and a clear project layout. No functional changes were deployed this month, but the groundwork accelerates upcoming implementation and future feature delivery.
December 2024
November 2024
18 Commits • 6 Features
Nov 1, 2024In 2024-11, I delivered a focused, career-ready algorithm toolkit for leejihoindaeyo/Uwith_DataStructure, emphasizing business value through reusable components, reliable implementations, and clear learning artifacts. Key features delivered include a consolidated Algorithm Practice Suite (distinct substring counting, substring utilities, and graph/tree traversal helpers), a robust Crane and Box Allocation (BOJ 1092) solution using sorting and simulation with edge-case handling for impossible allocations, and a Budget Allocation via Binary Search (BOJ 2512) approach to maximize per-request budgets under a total constraint. Additional work included Tree and Graph Data Structures and Traversal Utilities (build/delete lifecycle, leaf counting, path distances, DFS/BFS), skeleton/boilerplate creation for upcoming algorithms (1260.py, 11478.py, 11725.py), and Code Review Documentation and Guidelines to codify approaches and lessons learned. Major bugs fixed and resilience improvements focused on edge-case handling (notably in allocation logic) and traversal reliability, reducing regressions and improving maintainability. Overall impact: delivered a scalable, testable, and well-documented algorithm toolkit that accelerates problem solving, enhances onboarding, and strengthens code quality. Technologies and skills demonstrated include Python, algorithm design (sorting, binary search, graph/tree traversal), data-structure implementation, and documentation/code-review practices.
November 2024
18 Commits • 6 Features
Nov 1, 2024In 2024-11, I delivered a focused, career-ready algorithm toolkit for leejihoindaeyo/Uwith_DataStructure, emphasizing business value through reusable components, reliable implementations, and clear learning artifacts. Key features delivered include a consolidated Algorithm Practice Suite (distinct substring counting, substring utilities, and graph/tree traversal helpers), a robust Crane and Box Allocation (BOJ 1092) solution using sorting and simulation with edge-case handling for impossible allocations, and a Budget Allocation via Binary Search (BOJ 2512) approach to maximize per-request budgets under a total constraint. Additional work included Tree and Graph Data Structures and Traversal Utilities (build/delete lifecycle, leaf counting, path distances, DFS/BFS), skeleton/boilerplate creation for upcoming algorithms (1260.py, 11478.py, 11725.py), and Code Review Documentation and Guidelines to codify approaches and lessons learned. Major bugs fixed and resilience improvements focused on edge-case handling (notably in allocation logic) and traversal reliability, reducing regressions and improving maintainability. Overall impact: delivered a scalable, testable, and well-documented algorithm toolkit that accelerates problem solving, enhances onboarding, and strengthens code quality. Technologies and skills demonstrated include Python, algorithm design (sorting, binary search, graph/tree traversal), data-structure implementation, and documentation/code-review practices.
Activity
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Quality Metrics
Correctness69.6%
Maintainability68.6%
Architecture62.8%
Performance63.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
AlgorithmAlgorithm AnalysisAlgorithm ImplementationAlgorithmic ThinkingAlgorithmsBFSBinary SearchDFSData StructuresDepth First Search (DFS)Depth-First SearchDictionariesDictionaryDocumentationGraph Algorithms
Repositories Contributed To
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