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Copilot AI review requested due to automatic review settings December 21, 2025 13:30
@idoocs idoocs added core team Issues or pull requests from core team cpp Issues or Pull requests relate to .cpp code go Issues or Pull requests relate to .go code java Issues or Pull requests relate to .java code md Issues or Pull requests relate to .md files py Issues or Pull requests relate to .py code rs Issues or Pull requests relate to .rs code ts Issues or Pull requests relate to .ts code labels Dec 21, 2025
@yanglbme yanglbme merged commit 368986b into main Dec 21, 2025
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@yanglbme yanglbme deleted the dev branch December 21, 2025 13:32
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Pull request overview

This PR adds solutions to LeetCode problem #756 (Pyramid Transition Matrix) in multiple programming languages. The problem involves determining whether a pyramid can be built from a given bottom row using allowed triangular patterns through backtracking with memoization.

  • Implements six language solutions: Python, Java, C++, Go, TypeScript, and Rust
  • Uses memoization/dynamic programming to optimize the backtracking search
  • Includes comprehensive documentation in both Chinese and English with examples and complexity analysis

Reviewed changes

Copilot reviewed 8 out of 8 changed files in this pull request and generated no comments.

Show a summary per file
File Description
Solution.py Python solution using @cache decorator with itertools for generating combinations
Solution.java Java solution using bit manipulation for efficient pattern storage and StringBuilder for backtracking
Solution.cpp C++ solution using bit manipulation and unordered_map for memoization
Solution.go Go solution with bit manipulation and byte slice for backtracking state
Solution.ts TypeScript solution with similar bit manipulation approach and array-based state tracking
Solution.rs Rust solution using Vec for state management with proper ownership semantics
README.md Chinese documentation explaining the problem, approach, and solution complexity
README_EN.md English documentation with problem description, examples, and constraints

All solutions implement correct logic using memoized backtracking. The Python solution uses a functional approach with itertools, while other languages use an iterative backtracking approach with bit manipulation for efficient pattern matching. The code quality is high with appropriate use of language-specific features and data structures.


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3 participants