# Recent questions tagged algorithms 1
An algorithm is made up pf two modules $M1$ and $M2.$ If order of $M1$ is $f(n)$ and $M2$ is $g(n)$ then the order of algorithm is $max(f(n),g(n))$ $min(f(n),g(n))$ $f(n) + g(n)$ $f(n) \times g(n)$
2
The running time of an algorithm $T(n),$ where $’n’$ is the input size , is given by $T(n) = 8T(n/2) + qn,$ if $n>1$ $= p,$ if $n = 1$ Where $p,q$ are constants. The order of this algorithm is $n^{2}$ $n^{n}$ $n^{3}$ $n$
3
The average search time for hashing with linear probing will be less if the load factor Is far less than one Equals one Is far greater than one None of the above
4
The running time of an algorithm $T(n),$ where $’n’$ is the input size , is given by $T(n) = 8T(n/2) + qn,$ if $n>1$ $= p,$ if $n = 1$ Where $p,q$ are constants. The order of this algorithm is $n^{2}$ $n^{n}$ $n^{3}$ $n$
5
Consider the following C code segment: int Ls Prime(n) { int i,n; for(i=2;i<=sqrt(n);i++) if(n%i ==0) { printf( NOT Prime.\n ); return 0; } return 1; } Let $T(n)$ denote the number of times the for loop is executed by the program on input $n.$ ... $T(n) = O(\sqrt{n})$ and $T(n) = \Omega (1)$ $T(n) = O(n)$ and $T(n) = \Omega (\sqrt{n})$ None of these
6
Which of the following algorithm solve the all-pair shortest path problem? Dijakstra’s algorithm Floyd’s algorithm Prim’s algorithm Warshall’s algorithm
7
An algorithm is made up of two modules $M1$ and $M2.$ If order of $M1$ is $f(n)$ and $M2$ is $g(n)$ then he order of algorithm is $max(f(n),g(n))$ $min(f(n),g(n))$ $f(n) + g(n)$ $f(n) \times g(n)$
1 vote
8
Which type of algorithm is used to solve the "$8$ Queens" problem ? Greedy Dynamic Divide and conquer Backtracking
1 vote
9
The average search time of hashing, with linear probing will be less if the load factor : is far less than $1$ equals $1$ is far greater than $1$ none of the options
10
Merge sort uses : Divide-and-conquer Backtracking Heuristic approach Greedy approach
1 vote
11
Given two sorted list of size '$m$' and '$n$' respectively. The number of comparisons needed in the worst case by the merge sort algorithm will be : $m^{*}n$ minimum of $m, n$ maximum of $m, n$ $m+n-1$
12
Which of the following sorting algorithms does not have a worst case running time of $O(n​^2​)$? Insertion sort. Merge sort. Quick sort. Bubble sort.
13
A hash function $f$ defined as $f(\text{key})=\text{key mod }7$, with linear probing, insert the keys $37,38,72,48,98,11,56$ into a table indexed from $11$ will be stored in the location $3$ $4$ $5$ $6$
1 vote
14
A hash table has space for $100$ records. Then the probability of collision before the table is $10\%$ full, is $0.45$ $0.5$ $0.3$ $0.34$ (approximately)
15
Time complexity of an algorithm $T(n)$, where $n$ is the input size is given by $\begin{array}{ll}T(n) & =T(n-1)+1/n, \text{ if }n>1\\ & =1, \text{ otherwise} \end{array}$ The order of this algorithm is $\log n$ $n$ $n^2$ $n^n$
16
What is the type of the algorithm used in solving the $4$ Queens problem? Greedy Branch and Bound Dynamic Backtracking
17
Selection sort, quick sort is a stable sorting method True,True False,False True,False False,True
1 vote
18
Which of the following sorting procedures is the slowest? Quick Sort Merge Sort Shell Sort Bubble Sort
1 vote
19
Complexity of Kruskal's algorithm for finding minimum spanning tree of an undirected graph containing $n$ vertices and $m$ edges if the edges are sorted is: $O(mn)$ $O(m)$ $O(m+n)$ $O(n)$
20
Find the odd one out Merge Sort TVSP Problem Knapsack Problem OBST Problem
1 vote
21
The Knapsack problem belongs to which domain of problems? Optimization NP complete Linear Solution Sorting
22
The running time of Quick sort algorithm depends heavily on the selection of: No. of inputs Arrangement of elements in an array Size of elements Pivot Element
23
Two main measures for the efficiency of an algorithm are: Processor and Memory Complexity and Capacity Time and Space Data and Space
24
What is the solution to the recurrence $T(n)=T \bigg (\dfrac{n}{2} \bigg )+n$? $O(\log n)$ $O(n)$ $O(n\log n)$ None of these
25
The concept of order Big O is important because It can be used to decide the best algorithm that solves a given problem It is the lower bound of the growth rate of algorithm It determines the maximum size of a problem that can be solved in a given amount of time Both (A) and (B)
26
What is the running time of the following function (specified as a function of the input value)? void Function(int n){ int i=1; int s=1; while(s<=n){ i++; s=s+i; } } $O(n)$ $O(n^2)$ $O(1)$ $O(\sqrt n)$
27
$0/1$-Knapsack is a well known problem where, it is desired to get the maximum total profit by placing $n$ items (each item is having some weight and associated profit) into a knapsack of capacity $W$. The table given below shows the weights and associated profits for $5$ items, where one unit of ... $19$ $18$ $17$ $20$
The worst case running times of Insertion sort, Merge sort and Quick sort, respectively, are $\Theta(n \log n),\Theta(n \log n) \text{ and } \Theta(n^2)$ $\Theta(n^2),\Theta(n^2)\text{ and } \Theta(n \log n)$ $\Theta(n^2), \Theta(n \log n)\text{ and } \Theta(n \log n)$ $\Theta(n^2),\Theta(n\log n) \text{ and } \Theta(n^2)$
Which of the following standard algorithms is not Dynamic Programming based? Bellman-Ford Algorithm for single source shortest path Floyd Warshall Algorithm for all pairs shortest paths $0-1$ Knapsack problem Prim’s Minimum Spanning Tree
Four Matrices $M_1, M_2, M_3$ and $M_4$ of dimensions $p \times q$, $q \times r$, $r \times s$ and $s \times t$ ... $t=80$, then the number of scalar multiplications needed is $248000$ $44000$ $19000$ $25000$