Dynamic programming problems can be quite challenging, but with a systematic approach, you can improve your chances of solving them. Here are some general steps you can follow when approaching dynamic programming problems on LeetCode:
- Understand the problem: Before jumping into the problem, make sure you understand the problem statement, constraints, and any special requirements. Identify the input and output of the problem and the problem’s constraints, such as the size of the input, the range of the input, etc.
- Identify the subproblems: Once you understand the problem, try to break it down into smaller subproblems that can be solved independently. These subproblems should have some overlapping properties that can be exploited for dynamic programming.
- Define the recurrence relation: After identifying the subproblems, define the recurrence relation for each subproblem. This is a formula or equation that expresses the solution to a subproblem in terms of solutions to smaller subproblems.
- Identify the base cases: Determine the base cases, which are the smallest subproblems that can be solved without using the recurrence relation.
- Implement the solution: Using the recurrence relation and base cases, implement the solution to the problem. You can use a memoization technique or a bottom-up approach to store and compute the solutions to the subproblems.
- Analyze the time and space complexity: Finally, analyze the time and space complexity of your solution to ensure it meets the constraints of the problem.
Remember to practice and gain more experience with dynamic programming problems to become more familiar with this approach.