Welcome to Dynamic Programming CodeSnap

Dynamic Programming (DP) is a powerful optimization technique used for solving problems that exhibit overlapping subproblems and optimal substructure. It's widely used in competitive programming and interviews to solve complex recursive problems efficiently using memoization or bottom-up tabulation. From sequences to grids and partitions, DP helps break problems into manageable subproblems with minimal recomputation.

Table of Contents

• Climbing Stairs

  Solve the 'Climbing Stairs' problem using dynamic programming techniques.

• House Robber

  Solve the 'House Robber' problem using dynamic programming techniques.

• House Robber II

  Solve the 'House Robber II' problem using dynamic programming techniques.

• Fibonacci Number (Top-Down and Bottom-Up)

  Solve the 'Fibonacci Number (Top-Down and Bottom-Up)' problem using dynamic programming techniques.

• Longest Common Subsequence

  Solve the 'Longest Common Subsequence' problem using dynamic programming techniques.

• Longest Increasing Subsequence

  Solve the 'Longest Increasing Subsequence' problem using dynamic programming techniques.

• Partition Equal Subset Sum

  Solve the 'Partition Equal Subset Sum' problem using dynamic programming techniques.

• 0/1 Knapsack

  Solve the '0/1 Knapsack' problem using dynamic programming techniques.

• Coin Change

  Solve the 'Coin Change' problem using dynamic programming techniques.

• Coin Change II

  Solve the 'Coin Change II' problem using dynamic programming techniques.

• Minimum Path Sum

  Solve the 'Minimum Path Sum' problem using dynamic programming techniques.

• Unique Paths

  Solve the 'Unique Paths' problem using dynamic programming techniques.

• Edit Distance

  Solve the 'Edit Distance' problem using dynamic programming techniques.

• Word Break

  Solve the 'Word Break' problem using dynamic programming techniques.

• Palindrome Partitioning II

  Solve the 'Palindrome Partitioning II' problem using dynamic programming techniques.

• Decode Ways

  Solve the 'Decode Ways' problem using dynamic programming techniques.

• Best Time to Buy and Sell Stock

  Solve the 'Best Time to Buy and Sell Stock' problem using dynamic programming techniques.

• Best Time to Buy and Sell Stock II

  Solve the 'Best Time to Buy and Sell Stock II' problem using dynamic programming techniques.

• Maximum Subarray

  Solve the 'Maximum Subarray' problem using dynamic programming techniques.

• Burst Balloons

  Solve the 'Burst Balloons' problem using dynamic programming techniques.