DaleStudy/leetcode-study
Mar 2025 – Apr 2025
2 Months active
Languages Used
Swift
Technical Skills
AlgorithmData StructuresHash MapAlgorithm ImplementationArray ManipulationBacktracking
kut7728
PROFILE
Kut7728
Over a two-month period, this developer contributed to the DaleStudy/leetcode-study repository by building and optimizing seven algorithmic features and resolving one bug. Their work focused on implementing efficient solutions for common LeetCode problems using Swift, with an emphasis on linear-time algorithms and robust data structure choices such as sets, hash maps, and dynamic programming. They addressed challenges like duplicate detection, two-sum, top-k frequent elements, and dynamic programming for the House Robber problem. The developer also improved code maintainability by refactoring and cleaning up implementations, demonstrating strong skills in algorithm development, array manipulation, and problem-solving within a collaborative codebase.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
15Total
Bugs
1
Commits
15
Features
7
Lines of code
471
Activity Months2
Your Network
297 peopleSame Organization
@hanyang.ac.kr8
Work History
April 2025
12 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for DaleStudy/leetcode-study: Focused on delivering key algorithmic features, robust bug fixes, and improving problem-solving coverage. Achievements span dynamic programming, string/array problem solving, and core LeetCode algorithms, with a strong emphasis on code quality and maintainability.
12 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for DaleStudy/leetcode-study: Focused on delivering key algorithmic features, robust bug fixes, and improving problem-solving coverage. Achievements span dynamic programming, string/array problem solving, and core LeetCode algorithms, with a strong emphasis on code quality and maintainability.
April 2025
March 2025
3 Commits • 3 Features
Mar 1, 2025March 2025 – DaleStudy/leetcode-study: Delivered three Swift-based algorithmic features with linear-time performance, enhancing practice throughput and learning outcomes. Implementations include Contains Duplicate Detection (Set-based O(N)), Two Sum Solver (hash map O(N)), and Top K Frequent Elements Solver (frequency map + bucket sort, O(N)). No explicit bugs fixed documented this month. Impact: Faster, scalable solutions for common LeetCode patterns; improved code quality through concise data-structure choices and focused optimizations. Technologies/skills demonstrated: Swift language proficiency; Set and Dictionary usage; hash maps; frequency analysis; bucket sort; commit-driven development.
March 2025
3 Commits • 3 Features
Mar 1, 2025March 2025 – DaleStudy/leetcode-study: Delivered three Swift-based algorithmic features with linear-time performance, enhancing practice throughput and learning outcomes. Implementations include Contains Duplicate Detection (Set-based O(N)), Two Sum Solver (hash map O(N)), and Top K Frequent Elements Solver (frequency map + bucket sort, O(N)). No explicit bugs fixed documented this month. Impact: Faster, scalable solutions for common LeetCode patterns; improved code quality through concise data-structure choices and focused optimizations. Technologies/skills demonstrated: Swift language proficiency; Set and Dictionary usage; hash maps; frequency analysis; bucket sort; commit-driven development.
Activity
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Quality Metrics
Correctness96.0%
Maintainability90.6%
Architecture86.8%
Performance89.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Swift
Technical Skills
AlgorithmAlgorithm ImplementationArray ManipulationBacktrackingBinary Search TreeBit ManipulationCombinatoricsData StructuresDepth-First SearchDynamic ProgrammingHash MapHash TableRecursionSortingString Manipulation
Repositories Contributed To
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