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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
Whcih is an III-defined problem.
Question # 2
For which problems is Backtracking suitable
Question # 3
Which is solved by Dynamic Programming.
Question # 4
Which is an NP complete problem.
Question # 5
What does time complexity measrue.
Question # 6
Why are commonly used algorithms important.
Question # 7
What is the primary goal of algorithm design techniques.
Question # 8
Seach algorithm more efficinet for large datasets.
Question # 9
The Halting Problem is an example of.
Question # 10
How does Backtracking work.
Question # 11
What is the main advantage of Dynamic programming.
Question # 12
What is a key limitatio of Greedy Algorithms.
Question # 13
How do BFS and DFS differ.
Question # 14
Which is solved by dynamic programming.
Question # 15
NP hard problems are
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 |
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 |
| 2 |
Why is bubble sort not for large datasets. |
A.
Needs more memory
B.
O (n2) time complexity
C.
Works on sorted data only
D.
Can't handle numbers |
| 3 |
If P= NP ,this means |
A.
Some NP unsolvable
B.
all NP solvable inpolynomial time
C.
All NP unsolvable
D.
Same space complexity |
| 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 |
What is computational problem. |
A.
solved using algorithm
B.
Solved using creativity
C.
Has unclear input
D.
Has no process |
| 6 |
NP Problems can be |
A.
Solved in polynomial time
B.
Verified in polynomial time
C.
Solved in exponeitial timeonly
D.
Not verified |
| 7 |
What is the purpose of search algorithms |
A.
Arrange data
B.
Find secific data
C.
analyze nodes
D.
Save memory |
| 8 |
What defines a Greedy algorithm |
A.
Explore all solutions
B.
Make best local choice
C.
Store results
D.
Divide problems |
| 9 |
An algorithm with a time complexity of O(n log n): |
A.
Bubble sort
B.
Binary Search
C.
Merge Sort
D.
Insertion sort |
| 10 |
How does Backtracking work. |
A.
Break in to parts
B.
Make local choices
C.
Build and backtrack
D.
Store subproblems |
Test Questions