DaleStudy/leetcode-study
Mar 2025 – Apr 2025
2 Months active
Languages Used
Swift
Technical Skills
AlgorithmData StructuresHash MapAlgorithm ImplementationArray ManipulationBacktracking
kut7728
PROFILE
Kut7728
Over two months, Kut7728 contributed to the DaleStudy/leetcode-study repository by developing seven algorithmic features and resolving a key bug, focusing on efficient solutions to classic LeetCode problems. Working primarily in Swift, Kut7728 implemented linear-time algorithms for tasks such as duplicate detection, two-sum, and top-k frequent elements, leveraging data structures like sets, hash maps, and bucket sort. The work also included dynamic programming for the House Robber problem and string manipulation for anagram validation. Through careful refactoring and targeted bug fixes, Kut7728 improved code maintainability and demonstrated depth in algorithm implementation, array manipulation, and core data structure usage.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
15Total
Bugs
1
Commits
15
Features
7
Lines of code
471
Activity Months2
Your Network
259 people
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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