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MCQ's Test For Chapter 3 "Computer Science Ics Part 1 Chapter 3 Online Test"
Try The MCQ's Test For Chapter 3 "Computer Science Ics Part 1 Chapter 3 Online Test"
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Total Questions15
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Time Allowed20
Computer Science Ics Part 1 Chapter 3 Online Test
00:00
Question # 1
For which problems is Backtracking suitable
Question # 2
What is computational problem.
Question # 3
Which diagram shows P, NO, NP-hard,NP Complete
Question # 4
How does Linear Search work.
Question # 5
How does Backtracking work.
Question # 6
How does Backtracking work.
Question # 7
What does space complexity measure.
Question # 8
Which is an NP complete problem.
Question # 9
What is role of algorithm in problem solving.
Question # 10
What is the main advantage of Dynamic Programming.
Question # 11
Which alorithm finds node relationships in a graph.
Question # 12
What is generate and Test algorithm
Question # 13
How does Divide and conqurr work
Question # 14
What is the primary goal of algorithm design techniques.
Question # 15
Sovable problems differ becasue they.
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 |
Why use real life tasks in algorithm learning. |
A.
Show steps in life
B.
Make it harder
C.
Reduce interest
D.
Add confusion |
| 2 |
What defines a Greedy algorithm |
A.
Explore all solutions
B.
Make best local choice
C.
Store results
D.
Divide problems |
| 3 |
How do BFS and DFS differ. |
A.
BFS Stack, DFS -queue
B.
BFS -level , DFS -depth
C.
BFS Sort, DFS-Search
D.
BFS always slower |
| 4 |
How does bubble sort work |
A.
Select smallest and swap
B.
Swap adjacent if wrong
C.
Divide and merge
D.
Explore nodes level wise |
| 5 |
An algorithm with a time complexity of O(n log n): |
A.
Bubble sort
B.
Binary Search
C.
Merge Sort
D.
Insertion sort |
| 6 |
NP Problems can be |
A.
Solved in polynomial time
B.
Verified in polynomial time
C.
Solved in exponeitial timeonly
D.
Not verified |
| 7 |
How does Backtracking work. |
A.
Break in to parts
B.
Make local choices
C.
Build and backtrack
D.
Store subproblems |
| 8 |
What does “input” mean in a computational problem. |
A.
Result after processing
B.
Steps to solve
C.
Data at start
D.
Type of problem |
| 9 |
Which notation shows the upper bound of time complexity. |
A.
Omega
B.
Theta
C.
Big O
D.
Lambda |
| 10 |
Which technique is used in Merge sort. |
A.
Greedy
B.
Divide and conqurer
C.
Dynaimc Programming
D.
Back tracking |
Test Questions