- A O(N)
- B O(log N)
- C O(N^2)
- D O(N log N)
Time Complexity - Quiz
- A O(N)
- B O(log N)
- C O(N^2)
- D O(N log N)
- A O(N)
- B O(log N)
- C O(N^2)
- D O(N log N)
- A O(1)
- B O(log N)
- C O(N)
- D O(N^2)
- A O(N)
- B O(log N)
- C O(N^2)
- D O(1)
- A O(1)
- B O(log N)
- C O(N)
- D O(N^2)
- A O(1)
- B O(log N)
- C O(N)
- D O(N log N)
- A O(N)
- B O(log N)
- C O(N^2)
- D O(N log N)
- A O(1)
- B O(log N)
- C O(N)
- D O(N log N)
- A O(1)
- B O(log N)
- C O(N)
- D O(N log N)
Results:
🟢 Correct Answers: 🔴 Wrong Answers:
🟢 Correct Answers: 🔴 Wrong Answers:
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Quiz Analytics
Time Complexity - Quiz
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Time Taken: Questions: Answered: Not Answered:
Correct Answer:
Wrong Answer:
Percentage: %
- A. O(N)
- B. O(log N)
- C. O(N^2)
- D. O(N log N)
Remarks:
Explanation:
Merge sort has a time complexity of O(N log N), making it a stable and efficient sorting algorithm.
- A. O(N)
- B. O(log N)
- C. O(N^2)
- D. O(N log N)
Remarks:
Explanation:
Selection sort has a time complexity of O(N^2), making it less efficient compared to other sorting algorithms for large datasets.
- A. O(N)
- B. O(log N)
- C. O(N^2)
- D. O(N log N)
Remarks:
Explanation:
Shell sort has a time complexity of O(N^2) in its worst-case scenario, depending on the gap sequence chosen.
- A. O(1)
- B. O(log N)
- C. O(N)
- D. O(N^2)
Remarks:
Explanation:
The push operation in a stack has a constant-time complexity of O(1), making it efficient for adding elements to the top of the stack.
- A. O(N)
- B. O(log N)
- C. O(N^2)
- D. O(1)
Remarks:
Explanation:
In the best-case scenario, the time complexity of bubble sort is O(N), making it efficient for already sorted lists.
- A. O(1)
- B. O(log N)
- C. O(N)
- D. O(N^2)
Remarks:
Explanation:
The pop operation in a queue has a constant-time complexity of O(1), making it efficient for removing elements from the front of the queue.
- A. O(1)
- B. O(log N)
- C. O(N)
- D. O(N log N)
Remarks:
Explanation:
In the worst-case scenario, a hash table may have a time complexity of O(N) for searching an element, depending on collisions and hash function behavior.
- A. O(N)
- B. O(log N)
- C. O(N^2)
- D. O(N log N)
Remarks:
Explanation:
Merge sort has a time complexity of O(N log N), making it a stable and efficient sorting algorithm.
- A. O(1)
- B. O(log N)
- C. O(N)
- D. O(N log N)
Remarks:
Explanation:
Searching an element in a balanced binary search tree has a time complexity of O(log N), where N is the number of nodes.
- A. O(1)
- B. O(log N)
- C. O(N)
- D. O(N log N)
Remarks:
Explanation:
The union operation in a disjoint-set with path compression has a time complexity of O(log N), where N is the number of elements.