CS502-Midterm
1 / 50
The reason for introducing Sieve Technique algorithm is that it illustrates a very important special case of,
2 / 50
For the heap sort, access to nodes involves simple _______________ operations.
3 / 50
Before sweeping a vertical line in plane sweep approach, in start sorting of the points is done in increasing order of their _______coordinates.
4 / 50
Divide-and-conquer as breaking the problem into a small number of
5 / 50
A point p in 2-dimensional space is usually given by its integer coordinate(s)____________
6 / 50
Which may be a stable sort?
7 / 50
Algorithm analysts know for sure about efficient solutions for NP-complete problems.
8 / 50
Sorting can be in _________
9 / 50
A RAM is an idealized machine with ______________ random-access memory.
10 / 50
For Chain Matrix Multiplication we can not use divide and conquer approach because,
11 / 50
Algorithm is concerned with.......issues.
12 / 50
The running time of quick sort depends heavily on the selection of
13 / 50
The Knapsack problem belongs to the domain of _______________ problems.
14 / 50
A heap is a left-complete binary tree that conforms to the ___________
15 / 50
The array to be sorted is not passed as argument to the merge sort algorithm.
16 / 50
The analysis of Selection algorithm shows the total running time is indeed ________in n,
17 / 50
For the Sieve Technique we take time
18 / 50
The function f(n)= n(logn+1)/2 is asymptotically equivalent to n log n. Here Upper Bound means the function f(n) grows asymptotically ____________ faster than n log n.
19 / 50
What type of instructions Random Access Machine (RAM) can execute?
20 / 50
The sieve technique works where we have to find _________ item(s) from a large input.
21 / 50
Analysis of Selection algorithm ends up with,
22 / 50
Is it possible to sort without making comparisons?
23 / 50
Floor and ceiling are ____________ to calculate while analyzing algorithms.
24 / 50
The definition of Theta-notation relies on proving ___________asymptotic bound.
25 / 50
Efficient algorithm requires less computational…….
26 / 50
In Quick sort, we don’t have the control over the sizes of recursive calls
27 / 50
F (n) and g (n) are asymptotically equivalent. This means that they have essentially the same __________ for large n.
28 / 50
29 / 50
In Sieve Technique we do not know which item is of interest
30 / 50
In selection algorithm, because we eliminate a constant fraction of the array with each phase, we get the
31 / 50
What is the total time to heapify?
32 / 50
Quick sort is
33 / 50
Upper bound requires that there exist positive constants c2 and n0 such that f(n) ____ c2n for all n <= n0(ye question ghalat lag raha hai mujhae
34 / 50
The ancient Roman politicians understood an important principle of good algorithm design that is plan-sweep algorithm.
35 / 50
_________ is one of the few problems, where provable lower bounds exist on how fast we can sort.
36 / 50
Algorithm is a mathematical entity, which is independent of a specific machine and operating system.
37 / 50
We cannot make any significant improvement in the running time which is better than that of brute-force algorithm.
38 / 50
Due to left complete nature of binary tree, the heap can be stored in
39 / 50
In plane sweep approach, a vertical line is swept across the 2d-plane and _______structure is used for holding the maximal points lying to the left of the sweep line.
40 / 50
An algorithm is a mathematical entity that is dependent on a specific programming language.
41 / 50
Asymptotic growth rate of the function is taken over_________ case running time.
42 / 50
When we call heapify then at each level the comparison performed takes time
43 / 50
In which order we can sort?
44 / 50
_______________ is a graphical representation of an algorithm
45 / 50
46 / 50
In analysis of f (n) =n (n/5) +n-10 log n, f (n) is asymptotically equivalent to ________.
47 / 50
How many elements do we eliminate in each time for the Analysis of Selection algorithm?
48 / 50
Sieve Technique can be applied to selection problem?
49 / 50
In ____________ we have to find rank of an element from given input.
50 / 50
The function f(n)=n(logn+1)/2 is asymptotically equivalent to nlog n. Here Lower Bound means function f(n) grows asymptotically at ____________ as fast as nlog n.
Your score is
The average score is 40%
Restart quiz