CodingTestStudy2/Daily_Morning_Coding_Test
May 2026 – May 2026
1 Month active
Languages Used
Python
Technical Skills
PythonPython programmingalgorithm developmentdata structuresgraph theoryproblem solving
SangHyun Kim
PROFILE
Sanghyun Kim
Contributed to the CodingTestStudy2/Daily_Morning_Coding_Test repository by developing three end-to-end features focused on algorithmic problem solving and code maintainability. Built and refactored solutions for LeetCode challenges including Two Sum, 3Sum, and Harshad Number, introducing a digit-sum based Harshad checker and standardizing naming conventions for clarity. Implemented a directed graph edge score analysis to compute nodes with the highest incoming edge scores, and developed a solution for calculating total color value in overlapping segments. All work was completed in Python, emphasizing modular code structure, improved testability, and consistent commit practices to ensure traceability and readiness for continuous integration.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
3
Lines of code
194
Activity Months1
Your Network
39 peopleWork History
May 2026
6 Commits • 3 Features
May 1, 2026May 2026 monthly performance summary for CodingTestStudy2/Daily_Morning_Coding_Test: Delivered end-to-end enhancements across the LeetCode practice suite, graph analytics, and segment color calculations. Key refactors and naming standardization improved maintainability and future extensibility. All work is traceable via consistent commit messages (Day01–Day07) and prepared for CI/testing readiness.
6 Commits • 3 Features
May 1, 2026May 2026 monthly performance summary for CodingTestStudy2/Daily_Morning_Coding_Test: Delivered end-to-end enhancements across the LeetCode practice suite, graph analytics, and segment color calculations. Key refactors and naming standardization improved maintainability and future extensibility. All work is traceable via consistent commit messages (Day01–Day07) and prepared for CI/testing readiness.
May 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability86.6%
Architecture86.6%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
PythonPython programmingalgorithm developmentdata structuresgraph theoryproblem solving
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