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NSCT – Complexity & Efficiency Awareness MCQs

1. . Algorithmic complexity is:

(A) Encrypting data


(B) A measure of the amount of resources (time and space) an algorithm requires


(C) Compressing files


(D) Backup only




2. . Time complexity refers to:

(A) Compressing time


(B) Encrypting time


(C) The amount of computational time an algorithm takes as a function of input size


(D) Backup only




3. . Space complexity refers to:

(A) The amount of memory an algorithm uses as a function of input size


(B) Encrypting memory


(C) Compressing memory


(D) Backup only




4. . Big O notation describes:

(A) Encryption efficiency


(B) The upper bound of an algorithm's time or space complexity


(C) Compression ratio


(D) Backup only




5. . Best-case complexity refers to:

(A) The minimum time an algorithm takes for the most favorable input


(B) Encrypting best case


(C) Compressing best case


(D) Backup only




6. . Worst-case complexity refers to:

(A) Compressing worst case


(B) Encrypting worst case


(C) The maximum time an algorithm takes for the least favorable input


(D) Backup only




7. . Average-case complexity refers to:

(A) Compressing average case


(B) Encrypting average case


(C) The expected time an algorithm takes over all possible inputs


(D) Backup only




8. . Constant time complexity is:

(A) Compressing constant


(B) Encrypting constant


(C) O(1), where execution time does not depend on input size


(D) Backup only




9. . Linear time complexity is:

(A) Encrypting linearly


(B) O(n), where execution time increases proportionally with input size


(C) Compressing linearly


(D) Backup only




10. . Quadratic time complexity is:

(A) Backup only


(B) Encrypting quadratically


(C) Compressing quadratically


(D) O(n²), where execution time increases with the square of input size




11. . Logarithmic time complexity is:

(A) Backup only


(B) Encrypting logarithmically


(C) Compressing logarithmically


(D) O(log n), typical in divide-and-conquer algorithms like binary search




12. . Space-efficient algorithms:

(A) Minimize memory usage while performing computations


(B) Encrypt memory


(C) Compress memory


(D) Backup only




13. . Trade-off between time and space in algorithms means:

(A) Backup only


(B) Encrypting trade-off


(C) Compressing trade-off


(D) Reducing time may increase space usage, or reducing space may increase time




14. . Complexity awareness helps programmers to:

(A) Encrypt programs


(B) Choose efficient algorithms for better performance


(C) Compress programs


(D) Backup only




15. . Bubble sort has which time complexity in worst case?

(A) O(1)


(B) O(n²)


(C) O(log n)


(D) O(n)




16. . Binary search has which time complexity in worst case?

(A) O(1)


(B) O(log n)


(C) O(n²)


(D) O(n)




17. . Quick sort has which average time complexity?

(A) O(log n)


(B) O(n²)


(C) O(n log n)


(D) O(1)




18. . Efficiency in algorithm design aims to:

(A) Minimize execution time and memory usage


(B) Encrypt efficiently


(C) Compress efficiently


(D) Backup efficiently




19. . Big O notation ignores:

(A) Backup time


(B) Encryption time


(C) Compression ratios


(D) Constant factors and lower-order terms




20. . The main purpose of complexity and efficiency awareness is to:

(A) Compress files


(B) Encrypt data


(C) Understand and choose algorithms that optimize time and space for better program performance


(D) Backup tables




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