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The best algorithm to solve a given problem is one that requires less space in
memory and takes less time to complete its execution. But in practice it is not always possible to achieve both of these objectives. There may be more than one approach to solve a problem. One approach may require more space but less time to complete its execution. The 2nd approach may require less space but takes more time to complete execution. We choose 1st approach if time is a constraint and 2nd approach if space is a constraint. Thus we may have to sacrifice one at cost of the other. That is what we can say that there exists a time space trade among algorithm.
What is the time complexity of Merge sort and Heap sort algorithms? Time complexity of merge sort is O(N log2 N) Time complexity of heap sort is O(nlog2n)
Data array A has data series from 1,000,000 to 1 with step size 1, which is in perfect decreasing order. Data array B has data series from 1 to 1,000,000, which is in random order.
In the last subsection, we have implemented a stack by using an array. While a stack is implemented by using arrays, it suffers from the basic restriction of an array - i.e., its s
A binary tree of depth "d" is an almost complete binary tree if A) Every leaf in the tree is either at level "d" or at level "d-1" B) For any node "n" in the tree with a
floyd warshall algorithm
In the earlier unit, we have discussed about the arrays. Arrays are data structures of fixed size. Insertion & deletion involves reshuffling of array elements. Thus, arraymanipulat
Give example of assertion and abstract data type For illustration, consider Natural ADT whose carrier set is the set of non-negative integers and whose operations are the usual
What are circular queues? Circular queue: Static queues have a very large drawback that once the queue is FULL, even though we erase few elements from the "front" and relieve
what is boot algorithm and some example
program on function loading
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