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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
Which diagram shows P, NO, NP-hard,NP Complete
Question # 2
Which is solved by Dynamic Programming.
Question # 3
An algorithm with a time complexity of O(n log n):
Question # 4
Why use real life tasks in algorithm learning.
Question # 5
What is the primary goal of algorithm design techniques.
Question # 6
Why is bubble sort not for large datasets.
Question # 7
Whcih is a sorting algorithms.
Question # 8
For which problems is Backtrackign suitable.
Question # 9
What does space complexity measure.
Question # 10
Which notation shows the upper bound of time complexity.
Question # 11
The meanig of NP in computational complexity is.
Question # 12
What is a key limitatio of Greedy Algorithms.
Question # 13
How does Divide and conquere work.
Question # 14
What is the main advantage of Dynamic Programming.
Question # 15
Problems in NP and NP-hard are called.
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 |
Which is a Greedy Algorithm example |
A.
Fibonacci sequence
B.
Coin change
C.
Merge sort
D.
Puzzle solving |
| 2 |
What is the main advantage of Dynamic Programming. |
A.
Avoid redundant work
B.
Locally optmal results
C.
Sole independent problems
D.
Explore all options |
| 3 |
How does Divide and conquere work. |
A.
Make local chices
B.
Break ,solve, combine
C.
Store subproblem results
D.
Try alloptions, backtrack |
| 4 |
Which is an NP complete problem. |
A.
Sorting
B.
Knapsack
C.
GCD finding
D.
Binary search |
| 5 |
A seenario where Dynaimic progrmming proves most useful |
A.
Problem withou overlapping sub problems
B.
Problems solved by making local choices
C.
Problems with overlapping sub problems and optimal sbstructure
D.
Problem divided into independent sub problems |
| 6 |
What defines a Greedy algorithm |
A.
Explore all solutions
B.
Make best local choice
C.
Store results
D.
Divide problems |
| 7 |
Which diagram shows P, NO, NP-hard,NP Complete |
A.
Bar chart
B.
Pie chart
C.
Venn diagram
D.
Lne graph |
| 8 |
An algorithm with a time complexity of O(n log n): |
A.
Bubble sort
B.
Binary Search
C.
Merge Sort
D.
Insertion sort |
| 9 |
The meanig of NP in computational complexity is. |
A.
Non deterministic polynomial time
B.
Negative polynomial time
C.
No trivial polynomial time
D.
Numerical polynomial time |
| 10 |
What does space complexity measure. |
A.
Execution time
B.
Memory usage
C.
Number of steps
D.
Result accuracy |
Test Questions