You use Memoization (caching) to store the results of recursive branches. If the program needs to evaluate a branch it has seen before, it retrieves the answer instantly instead of branching again.
O(2^N) Exponential Time: The Danger of Naive Recursion
How do you optimize an O(2^N) algorithm?
The answer
More FAQs in O(2^N) Exponential Time: The Danger of Naive Recursion
It is a complexity where the processing time doubles for every single additional element added to the input data.
Quadratic time grows predictably. N=50 in O(N^2) is 2500 operations. N=50 in O(2^N) is over 1 Quadrillion operations, making it physically impossible to compute.
It is almost always caused by recursive functions that make two recursive calls to themselves, creating an exponentially growing tree of execution.
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