First Year Computer Science Chapter 3 Online MCQ Test for 1st Year Computer Science Chapter 3 (Data Communication)

ICS Part 1 Computer Science Chapter 3 Test

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ICS Part 1 Computer Science Chapter Wise Test

MCQ's Test For Chapter 3 "Computer Science Ics Part 1 Chapter 3 Online Test"

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Computer Science Ics Part 1 Chapter 3 Online Test

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Question # 1

What is a key limitatio of Greedy Algorithms.

Question # 2

What does page rank algorithm analyze.

Question # 3

Why are commonly used algorithms important.

Question # 4

What is generate and Test algorithm

Question # 5

For which problems is Backtracing suitable.

Question # 6

The Halting Problem is an example of.

Question # 7

Why is bubble sort not for large datasets.

Question # 8

Why is tractability important.

Question # 9

An algorithm with a time complexity of  O(n log n):

Question # 10

How does Divide and conqurr work

Question # 11

Which diagram shows P, NO, NP-hard,NP Complete

Question # 12

When is Generate and Test best.

Question # 13

How does bubble sort work

Question # 14

NP- complete  matters because.

Question # 15

What is the primary goal of algorithm design techniques.

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11th Class ICS Computer Science Chapter 3 MCQ's Test

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ICS Part 1 Computer Science (New Book) Chapter 3 Important MCQ's

Sr.# Question Answer
1

What is the purpose of search algorithms

A.

Arrange data

B.

Find secific data

C.

analyze nodes

D.

Save memory

2

Tractability depends on 

A.

Inputs

B.

Complexity

C.

Outputs

D.

Algorthm type

3

The characteristic of a well defined problem is.

A.

Ambiguous goals and uncelear requirements

B.

Vegue processes and inputs

C.

Clear goas, inpus, processes, and oututs 

D.

Undrined solutions

4

How does Divide and conquere work.

A.

Make local chices

B.

Break ,solve, combine

C.

Store subproblem results

D.

Try alloptions, backtrack

5

What does “input” mean in a computational problem.

A.

Result after processing

B.

Steps to solve

C.

Data at start

D.

Type of problem

6

What is the main advantage of Dynamic Programming.

A.

Avoid redundant work

B.

Locally optmal results

C.

Sole independent problems

D.

Explore all options

7

What defines a Greedy algorithm

A.

Explore all solutions

B.

Make best local choice

C.

Store results

D.

Divide problems

8

P vs NP asks if

A.

Fast solutions are in NP

B.

Check complexity

C.

Debug rrors

D.

Improve hardware

9

What is outpout when checking if 8 is even.

A.

Found at 2

B.

Even

C.

Odd

D.

Yes

10

For which problems is Backtrackign suitable.

A.

Optimal substructure

B.

Explore all combinations

C.

One optimal choice

D.

No overlapping problems

Test Questions

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