ssafy16codingteststudy/1st_algorithm
Feb 2025 – Mar 2025
2 Months active
Languages Used
Java
Technical Skills
AlgorithmAlgorithm DesignAlgorithmsBFSBreadth-First Search (BFS)Data Structures
jun10920
PROFILE
Jun10920
During a two-month period, Abide developed and expanded the ssafy16codingteststudy/1st_algorithm repository, focusing on algorithmic problem-solving templates and educational tooling. He implemented a suite of features in Java, emphasizing tree algorithms, dynamic programming, and graph traversal techniques such as BFS and DFS. Abide delivered solutions for a range of BOJ problems, including parent discovery, safe zone analysis, and minimum cost pathfinding, while also introducing matrix exponentiation and modular arithmetic modules. His work prioritized code readability, maintainability, and edge-case handling, resulting in a scalable, reusable reference that accelerates onboarding and supports efficient interview preparation for algorithmic challenges.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
16Total
Bugs
0
Commits
16
Features
10
Lines of code
2,164
Activity Months2
Your Network
1016 people
Work History
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 Monthly Summary for ssafy16codingteststudy/1st_algorithm. Focused on expanding the Algorithmic Problem-Solving Toolkit to improve interview readiness and practice efficiency. Delivered broad coverage across core algorithmic patterns, including dynamic programming sequences, matrix exponentiation for Fibonacci, BFS-based simulations, and practical solutions to BOJ problems (Baby Shark, Tree Diameter, BST Post-order traversal). This work enhances reusability of problem-solving templates, accelerates onboarding, and reinforces the repository as a reliable reference for algorithm practice. Commits implementing the feature are recorded below, with traceable hashes. Major bugs fixed: none in this period; the emphasis was feature expansion.
2 Commits • 1 Features
Mar 1, 2025March 2025 Monthly Summary for ssafy16codingteststudy/1st_algorithm. Focused on expanding the Algorithmic Problem-Solving Toolkit to improve interview readiness and practice efficiency. Delivered broad coverage across core algorithmic patterns, including dynamic programming sequences, matrix exponentiation for Fibonacci, BFS-based simulations, and practical solutions to BOJ problems (Baby Shark, Tree Diameter, BST Post-order traversal). This work enhances reusability of problem-solving templates, accelerates onboarding, and reinforces the repository as a reliable reference for algorithm practice. Commits implementing the feature are recorded below, with traceable hashes. Major bugs fixed: none in this period; the emphasis was feature expansion.
March 2025
February 2025
14 Commits • 9 Features
Feb 1, 2025February 2025: Delivered a cohesive algorithmic reference for the 1st_algorithm repo, with a strong emphasis on tree algorithms, BFS-based problem solving, and DP patterns. Implemented and refactored multiple BOJ problems across modules (11725, 2468, 4485, 13398, 15988, 19638, 10840, plus Week 2/3 problem sets) with a focus on correctness, readability, and maintainability. Expanded problem coverage to include matrix exponentiation, modular arithmetic, quadtree, and fractal generation, and improved edge-case handling and testability. Result: faster solution delivery, clearer code, and a scalable foundation for future sprints; a solid business value for interview prep and educational tooling.
February 2025
14 Commits • 9 Features
Feb 1, 2025February 2025: Delivered a cohesive algorithmic reference for the 1st_algorithm repo, with a strong emphasis on tree algorithms, BFS-based problem solving, and DP patterns. Implemented and refactored multiple BOJ problems across modules (11725, 2468, 4485, 13398, 15988, 19638, 10840, plus Week 2/3 problem sets) with a focus on correctness, readability, and maintainability. Expanded problem coverage to include matrix exponentiation, modular arithmetic, quadtree, and fractal generation, and improved edge-case handling and testability. Result: faster solution delivery, clearer code, and a scalable foundation for future sprints; a solid business value for interview prep and educational tooling.
Activity
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Quality Metrics
Correctness95.0%
Maintainability80.0%
Architecture80.0%
Performance88.8%
AI Usage21.2%
Skills & Technologies
Programming Languages
Java
Technical Skills
AlgorithmAlgorithm DesignAlgorithmsBFSBinary Search TreeBreadth-First SearchBreadth-First Search (BFS)Data StructuresDepth First SearchDepth-First SearchDivide and ConquerDynamic ProgrammingFractal GenerationGraph TheoryGraph Traversal
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