# Divide and Conquer Method vs Dynamic Programming

Divide and Conquer Method Dynamic Programming
1.It deals (involves) three steps at each level of recursion:
Divide the problem into a number of subproblems.
Conquer the subproblems by solving them recursively.
Combine the solution to the subproblems into the solution for original subproblems.
1.It involves the sequence of four steps:
• Characterize the structure of optimal solutions.
• Recursively defines the values of optimal solutions.
• Compute the value of optimal solutions in a Bottom-up minimum.
• Construct an Optimal Solution from computed information.
2. It is Recursive. 2. It is non Recursive.
3. It does more work on subproblems and hence has more time consumption. 3. It solves subproblems only once and then stores in the table.
4. It is a top-down approach. 4. It is a Bottom-up approach.
5. In this subproblems are independent of each other. 5. In this subproblems are interdependent.
6. For example: Merge Sort & Binary Search etc. 6. For example: Matrix Multiplication.

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