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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.
Example of pre order traversal: Reading of a book, since we do not read next chapter unless we complete all sections of previous chapter & all its sections. Figure : Rea
. Create a decision table that describes the movement of inventory
Double Linked List In a doubly linked list, also known as 2 way lists, each node is separated into 3 parts. The first part is called last pointer field. It has the address of t
compare two functions n and 2n for various values of n. determine when second becomes larger than first
According to this, key value is divided by any fitting number, generally a prime number, and the division of remainder is utilized as the address for the record. The choice of s
Q. Describe the adjacency matrix and make the same for the given undirected graph. Ans: The representation of Adjacency Matrix: This representation consists of
Advantages of dry running a flowchart When dry running a flowchart it's advisable to draw up a trace table illustrating how variables change their values at every stage in the
What do you mean by complexity of an algorithm? The complexity of an algorithm M is the function f(n) which gives the running time and/or storage space need of the algorithm i
How will you represent a max-heap sequentially? Max heap, also known as the descending heap, of size n is an almost complete binary tree of n nodes such that the content of eve
The minimum cost spanning tree has broad applications in distinct fields. It represents several complicated real world problems such as: 1. Minimum distance for travelling all o
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