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This approach leverages dynamic programming techniques to break down the problem into overlapping subproblems and solve them using a bottom-up manner. The core idea is to store the results of subproblems to avoid redundant computations, therefore optimizing the solution.
Time Complexity: O(n)
Space Complexity: O(n)
1// JavaScript code for dynamic programming approach
In JavaScript, which is inherently dynamic, we utilize arrays to manage the state of the computation across function calls, incrementally building the solution.
The greedy approach aims to find a solution by making the most favorable choice at every stage, intending to reach an overall optimal solution. This approach might not always work for all types of problems but can provide simpler solutions where applicable.
Time Complexity: O(n)
Space Complexity: O(1)
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In C#, the greedy algorithm is expressed using a loop, iterating through and making optimal selections as per current criteria, reflecting changes instantly.