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Stacks are often used in evaluation of arithmetic expressions. An arithmetic expression contains operands & operators. Polish notations are evaluated through stacks. Conversions of different notations (Prefix, Postfix, Infix) in one another are performed by using stacks. Stacks are extensively used inside computer while recursive functions are called. The computers appraise arithmetic expression written into infix notation in two steps. First one, it converts the infix expression to postfix expression & then this evaluates the postfix expression. In each of step, stack is utilized to accomplish the task.
Write an algorithm for multiplication of two sparse matrices using Linked Lists.
Write an algorithm for getting solution to the Tower's of Hanoi problem. Explain the working of your algorithm (with 4 disks) with appropriate diagrams. Ans: void Hanoi(int
Q. Give the algorithm for the selection sort. Describe the behaviours of selection sort when the input given is already sorted.
To delete an element in the list at the end, we can delete it without any difficult. But, assume if we desire to delete the element at the straining or middle of the list, then, we
Consider the digraph G with three vertices P1,P2 and P3 and four directed edges, one each from P1 to P2, P1 to P3, P2 to P3 and P3 to P1. a. Sketch the digraph. b. Find the a
You are given two jugs, a 4-gallon one and a 3-gallon one. Neither has any measuring marker on it. There is a tap that can be used to fill the jugs with water. How can you get exac
Define Dynamic Programming Dynamic programming is a method for solving problems with overlapping problems. Typically, these sub problems arise from a recurrence rel
Q. Explain that how do we implement two stacks in one array A[1..n] in such a way that neither the stack overflows unless the total number of elements in both stacks together is n.
Sorting Algorithm A sorting algorithm is an algorithm which puts elements of a list in a certain order. The most-used orders are numerical order and lexicographical order. Eff
The complexity Ladder: T(n) = O(1). It is called constant growth. T(n) does not raise at all as a function of n, it is a constant. For illustration, array access has this c
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