DaleStudy/leetcode-study
Nov 2025 – Feb 2026
4 Months active
Languages Used
Java
Technical Skills
JavaJava programmingSoftware Developmentalgorithm designalgorithm developmentdata structures
ymir0804
PROFILE
Ymir0804
Over four months, contributed to the DaleStudy/leetcode-study repository by developing a suite of algorithmic solutions and utilities focused on core data structures and problem-solving patterns. Implemented features such as hash-based array algorithms, dynamic programming for optimization problems, recursive tree depth calculation, and backtracking for combinatorial tasks, all in Java. Emphasized clean code practices through consistent linting, formatting, and POSIX compliance, improving maintainability and onboarding. Addressed code quality by standardizing line endings and removing unused imports. The work demonstrated strong skills in algorithm design, recursion, and version control, resulting in a robust, reusable library for technical interview preparation.
Overall Statistics
Feature vs Bugs
92%Features
Repository Contributions
33Total
Bugs
1
Commits
33
Features
11
Lines of code
500
Activity Months4
Your Network
323 peopleSame Organization
@kakao.com34
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 performance summary for DaleStudy/leetcode-study: Delivered a Binary Tree Depth Calculation Utility implementing a recursive algorithm to compute the maximum depth of a binary tree. The utility handles null nodes and correctly evaluates left and right subtrees to determine depth, enabling faster analysis of tree-based LeetCode problems. The work is encapsulated in a focused commit and contributes to a growing library of reusable problem-solving utilities in the repository, improving research productivity and study consistency. No major bugs reported; feature-focused iteration with clear testing coverage implied.
1 Commits • 1 Features
Feb 1, 2026February 2026 performance summary for DaleStudy/leetcode-study: Delivered a Binary Tree Depth Calculation Utility implementing a recursive algorithm to compute the maximum depth of a binary tree. The utility handles null nodes and correctly evaluates left and right subtrees to determine depth, enabling faster analysis of tree-based LeetCode problems. The work is encapsulated in a focused commit and contributes to a growing library of reusable problem-solving utilities in the repository, improving research productivity and study consistency. No major bugs reported; feature-focused iteration with clear testing coverage implied.
February 2026
January 2026
11 Commits • 2 Features
Jan 1, 2026January 2026 performance summary for DaleStudy/leetcode-study. Delivered a core Algorithmic Problem Solvers Library with backtracking and dynamic programming solutions (Combination Sum, Decode Ways, Maximum Subarray) and a newline handling fix. Added a Merge Two Sorted Linked Lists utility with refactoring for linting compliance. Implemented Code Quality and Stability Improvements by standardizing line endings and addressing lint issues across the codebase. These efforts improved solution coverage for common interview problems, ensured code reliability, and reduced maintenance burden, enabling faster onboarding for contributors and more robust learning materials.
January 2026
11 Commits • 2 Features
Jan 1, 2026January 2026 performance summary for DaleStudy/leetcode-study. Delivered a core Algorithmic Problem Solvers Library with backtracking and dynamic programming solutions (Combination Sum, Decode Ways, Maximum Subarray) and a newline handling fix. Added a Merge Two Sorted Linked Lists utility with refactoring for linting compliance. Implemented Code Quality and Stability Improvements by standardizing line endings and addressing lint issues across the codebase. These efforts improved solution coverage for common interview problems, ensured code reliability, and reduced maintenance burden, enabling faster onboarding for contributors and more robust learning materials.
December 2025
8 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for DaleStudy/leetcode-study: Delivered code quality improvements and foundational algorithm practice, with concrete commits across linting, formatting, and core data structure problems. Key features: 1) Code Quality Improvements (linting across the codebase, formatting fixes, EOF newline additions, and removal of unused imports) with commits 08b539e136977fea4182eb0a02cff2e8d0bc7fd6; 5cb9b9762a7d57f74af0e7256d78a283720e20f4; e0d4bd9ef7c14e5cc164e4147df232e46eda8d72. 2) Algorithmic Practice: Implementations for Product of Array Except Self, 3Sum, BST validation, palindrome check, and bit-counting with commits 744b5ac4312f5c0cacaefaa4c1b12ba0716dd23f; 9658082dd4f18ec0342d1c294da230bb5bc17672; 8261cc5e8c1b769c685e48920ac3ea4d8b7ed9f9; f0415489a560fe0be5860f3899e4ef361304931f; 5f65c66e079f27b721cc989acf5d59234b256978. Overall impact: improved maintainability, reduced lint warnings, and demonstrated practical algorithm mastery, enabling faster feature iteration and higher code quality for future work. Technologies/skills: linting/formatting and static analysis, core DS/algorithms, clean-code practices, and commit-driven development.
8 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for DaleStudy/leetcode-study: Delivered code quality improvements and foundational algorithm practice, with concrete commits across linting, formatting, and core data structure problems. Key features: 1) Code Quality Improvements (linting across the codebase, formatting fixes, EOF newline additions, and removal of unused imports) with commits 08b539e136977fea4182eb0a02cff2e8d0bc7fd6; 5cb9b9762a7d57f74af0e7256d78a283720e20f4; e0d4bd9ef7c14e5cc164e4147df232e46eda8d72. 2) Algorithmic Practice: Implementations for Product of Array Except Self, 3Sum, BST validation, palindrome check, and bit-counting with commits 744b5ac4312f5c0cacaefaa4c1b12ba0716dd23f; 9658082dd4f18ec0342d1c294da230bb5bc17672; 8261cc5e8c1b769c685e48920ac3ea4d8b7ed9f9; f0415489a560fe0be5860f3899e4ef361304931f; 5f65c66e079f27b721cc989acf5d59234b256978. Overall impact: improved maintainability, reduced lint warnings, and demonstrated practical algorithm mastery, enabling faster feature iteration and higher code quality for future work. Technologies/skills: linting/formatting and static analysis, core DS/algorithms, clean-code practices, and commit-driven development.
December 2025
November 2025
13 Commits • 6 Features
Nov 1, 20252025-11 Monthly Summary – DaleStudy/leetcode-study Key features delivered: - Hash-based Array Algorithm Solutions: duplicate detection, Two Sum, Top K Frequent Elements. Commits: cc29a919c32b94c5b84304eee0c60790eabf41a7; 151f5c1e7f41acfb1be44c53b9154d8c00437e12; 5d7cff75bba5249d8207304e53876442fa6ac99a; 814fa1ec95a839737af3f72ffaf526900955c337; 267674e2ed21475714002cfa51be88d3773999c3. - Longest Consecutive Sequence in Array: hash-based O(n) solution using a HashSet for fast lookups. Commits: 29891065e2bd0078daa95e8959428e8918a91850; 2198bdc99d54d8e6f3f5b8339d6d58969234cf22. - House Robber DP: dynamic programming solution to optimize decisions across non-adjacent houses. Commit: 4e5b3625a6e02bfbdde71bd37e520db48698e062. - Anagrams Check: string-anagram verification via character-set comparison. Commit: d960abebcda411ae48a2fed9ca99ba6cf93ac52d. - Climbing Stairs DP: DP approach to count distinct ways to climb n steps. Commit: faf86af1fbb768f7ea95d137f728c1543d384da0. - Code Quality and Maintenance: POSIX newline compliance, file renames for consistency, and linting rule updates. Commits: e8ba3456234d288260a08d44919fa4827d0b8b09; cc7207fe2cdaf1057f58b8eaf520fa964340ff58; 10a94974e6271d716a4dffbf8144686ba891cda2. Major bugs fixed: - Linting, formatting, and naming consistency improvements to reduce noise and enhance maintainability. Overall impact and accomplishments: - Delivered scalable, efficient algorithms and reliable code quality improvements; strengthened maintainability, readability, and onboarding for new contributors; improved performance for common problem-solving tasks. Technologies/skills demonstrated: - Hash-based data structures (HashSet/HashMap), dynamic programming, string processing, and code quality tooling (POSIX standards, linting).
November 2025
13 Commits • 6 Features
Nov 1, 20252025-11 Monthly Summary – DaleStudy/leetcode-study Key features delivered: - Hash-based Array Algorithm Solutions: duplicate detection, Two Sum, Top K Frequent Elements. Commits: cc29a919c32b94c5b84304eee0c60790eabf41a7; 151f5c1e7f41acfb1be44c53b9154d8c00437e12; 5d7cff75bba5249d8207304e53876442fa6ac99a; 814fa1ec95a839737af3f72ffaf526900955c337; 267674e2ed21475714002cfa51be88d3773999c3. - Longest Consecutive Sequence in Array: hash-based O(n) solution using a HashSet for fast lookups. Commits: 29891065e2bd0078daa95e8959428e8918a91850; 2198bdc99d54d8e6f3f5b8339d6d58969234cf22. - House Robber DP: dynamic programming solution to optimize decisions across non-adjacent houses. Commit: 4e5b3625a6e02bfbdde71bd37e520db48698e062. - Anagrams Check: string-anagram verification via character-set comparison. Commit: d960abebcda411ae48a2fed9ca99ba6cf93ac52d. - Climbing Stairs DP: DP approach to count distinct ways to climb n steps. Commit: faf86af1fbb768f7ea95d137f728c1543d384da0. - Code Quality and Maintenance: POSIX newline compliance, file renames for consistency, and linting rule updates. Commits: e8ba3456234d288260a08d44919fa4827d0b8b09; cc7207fe2cdaf1057f58b8eaf520fa964340ff58; 10a94974e6271d716a4dffbf8144686ba891cda2. Major bugs fixed: - Linting, formatting, and naming consistency improvements to reduce noise and enhance maintainability. Overall impact and accomplishments: - Delivered scalable, efficient algorithms and reliable code quality improvements; strengthened maintainability, readability, and onboarding for new contributors; improved performance for common problem-solving tasks. Technologies/skills demonstrated: - Hash-based data structures (HashSet/HashMap), dynamic programming, string processing, and code quality tooling (POSIX standards, linting).
Activity
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Quality Metrics
Correctness96.4%
Maintainability92.8%
Architecture92.8%
Performance92.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
Algorithm DevelopmentJavaJava programmingSoftware Developmentalgorithm designalgorithm developmentbacktrackingclean code practicesdata structuresdynamic programmingproblem solvingproblem-solvingrecursionsoftware developmentstring manipulation
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