DaleStudy/leetcode-study
Jul 2025 – Aug 2025
2 Months active
Languages Used
Java
Technical Skills
AlgorithmAlgorithm ImplementationArray ManipulationArrayListBucket SortCode Formatting
J Lee
PROFILE
J Lee
During a two-month period, Jae Won contributed to the DaleStudy/leetcode-study repository by developing five algorithmic features and addressing three bugs, primarily using Java. Jae Won focused on optimizing classic problems such as Two Sum and Top K Frequent Elements, implementing efficient solutions with HashMap and bucket sort to improve runtime performance. Additional work included dynamic programming for Climbing Stairs and array manipulation for Product of Array Except Self. Beyond feature development, Jae Won maintained code quality through formatting cleanups and repository hygiene, demonstrating attention to maintainability and standards. The work reflects solid depth in algorithms, data structures, and code organization.
Overall Statistics
Feature vs Bugs
63%Features
Repository Contributions
9Total
Bugs
3
Commits
9
Features
5
Lines of code
164
Activity Months2
Your Network
251 people
Work History
August 2025
1 Commits
Aug 1, 2025August 2025 monthly summary for DaleStudy/leetcode-study: focused on repo hygiene and non-functional formatting cleanup; no new features or user-facing changes implemented this month.
1 Commits
Aug 1, 2025August 2025 monthly summary for DaleStudy/leetcode-study: focused on repo hygiene and non-functional formatting cleanup; no new features or user-facing changes implemented this month.
August 2025
July 2025
8 Commits • 5 Features
Jul 1, 2025July 2025 monthly summary for DaleStudy/leetcode-study: Focused on delivering efficient algorithms, improving runtime performance, and enhancing code quality to support scalable practice problems. Key accomplishments span linear-time solutions, algorithmic breadth, and maintainability improvements that collectively increase value for interview prep and knowledge transfer.
July 2025
8 Commits • 5 Features
Jul 1, 2025July 2025 monthly summary for DaleStudy/leetcode-study: Focused on delivering efficient algorithms, improving runtime performance, and enhancing code quality to support scalable practice problems. Key accomplishments span linear-time solutions, algorithmic breadth, and maintainability improvements that collectively increase value for interview prep and knowledge transfer.
Activity
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Quality Metrics
Correctness86.6%
Maintainability82.2%
Architecture77.8%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
AlgorithmAlgorithm ImplementationArray ManipulationArrayListBucket SortCode FormattingData StructuresDynamic ProgrammingHashMapString Manipulation
Repositories Contributed To
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