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Enhanced Competitive Programming Study Guide

This document provides comprehensive enhancements to the existing Sample.md files across different algorithmic topics.

Summary of Enhancements Made

1. Sorting & Searching (python/Sorting/Sample.md)

Added:

  • Advanced array comparison patterns
  • Segment tree integration with sorting
  • Inversion count techniques
  • Radix sort for special cases
  • Merge sort for custom sorting with auxiliary data
  • Advanced coordinate compression with duplicates
  • Two-pointer with dynamic array
  • Sorting optimization strategies (hybrid approaches)
  • Cache-friendly sorting tips

2. Greedy Algorithms (python/Greedy/Sample.md)

Added:

  • Matroid greedy verification
  • Activity selection variants (weighted)
  • Job sequencing with deadlines (enhanced)
  • Huffman coding pattern
  • Fractional knapsack greedy
  • String rearrangement edge cases
  • Greedy + DP hybrids
  • Proof techniques for greedy correctness
  • Common greedy failures and why

3. Binary/N-ary Tree (python/Binary Tree/Sample.md)

Added:

  • Morris Traversal (O(1) space tree traversal)
  • Thread Binary Tree
  • AVL/Red-Black tree basics
  • Segment tree on trees
  • Virtual tree construction
  • Link-Cut trees overview
  • Fenwick tree on tree structures
  • Tree flattening techniques
  • XOR basis on tree paths
  • Treap/Cartesian tree patterns

4. Dynamic Programming (python/Dynamic Programming/Sample.md)

Added:

  • Matrix chain multiplication with memoization
  • Convex hull trick details
  • CHT with queries
  • Knuth-Yao speedup
  • Subset enumeration optimization
  • DP with profile compression
  • Tree DP with heavy-light decomposition
  • DP on permutations
  • Meet-in-middle DP
  • Tiling and counting problems
  • Broken profile DP
  • DP optimization: Four-Russian trick

5. Graph Algorithms (python/Graph/Sample.md)

Added:

  • 2-SAT solver
  • Bridges and articulation points (Tarjan)
  • Vertex connectivity
  • Planar graph detection
  • Euler characteristic
  • Max clique approximation
  • Network flow applications (practical)
  • Push-relabel algorithm (alternative to Dinic)
  • Capacity scaling
  • Successive shortest paths
  • Minimum cost circulation
  • Chinese postman problem
  • Gomory-Hu tree
  • Graph coloring heuristics