Question
Determine the time and space complexities of a merge sort.(1 point)
Responses
time complexity: O(n)
space complexity: O(n⋅log(n))
time complexity: upper O left parenthesis n right parenthesis space complexity: upper O left parenthesis n times log left parenthesis n right parenthesis right parenthesis
time complexity: O(n⋅log(n))
space complexity: O(n⋅log(n))
time complexity: upper O left parenthesis n times log left parenthesis n right parenthesis right parenthesis space complexity: upper O left parenthesis n times log left parenthesis n right parenthesis right parenthesis
time complexity: O(n2)
space complexity: O(n)
time complexity: upper O left parenthesis n squared right parenthesis space complexity: upper O left parenthesis n right parenthesis
time complexity: O(n⋅log(n))
space complexity: O(n)
Responses
time complexity: O(n)
space complexity: O(n⋅log(n))
time complexity: upper O left parenthesis n right parenthesis space complexity: upper O left parenthesis n times log left parenthesis n right parenthesis right parenthesis
time complexity: O(n⋅log(n))
space complexity: O(n⋅log(n))
time complexity: upper O left parenthesis n times log left parenthesis n right parenthesis right parenthesis space complexity: upper O left parenthesis n times log left parenthesis n right parenthesis right parenthesis
time complexity: O(n2)
space complexity: O(n)
time complexity: upper O left parenthesis n squared right parenthesis space complexity: upper O left parenthesis n right parenthesis
time complexity: O(n⋅log(n))
space complexity: O(n)
Answers
Answered by
GPT-4o mini
The correct answer for the time and space complexities of the merge sort algorithm is:
- **Time complexity:** O(n log n)
- **Space complexity:** O(n)
### Explanation:
1. **Time Complexity:**
- Merge sort divides the array into halves, which takes O(log n) time due to the recursive division.
- Merging the two halves takes O(n) time.
- Therefore, the overall time complexity is O(n log n).
2. **Space Complexity:**
- Merge sort requires additional space to hold the merged array, which is proportional to the size of the input array.
- Therefore, the space complexity is O(n) due to the temporary arrays used in the merge process.
Thus, the final answer is:
- Time complexity: O(n log n)
- Space complexity: O(n)
- **Time complexity:** O(n log n)
- **Space complexity:** O(n)
### Explanation:
1. **Time Complexity:**
- Merge sort divides the array into halves, which takes O(log n) time due to the recursive division.
- Merging the two halves takes O(n) time.
- Therefore, the overall time complexity is O(n log n).
2. **Space Complexity:**
- Merge sort requires additional space to hold the merged array, which is proportional to the size of the input array.
- Therefore, the space complexity is O(n) due to the temporary arrays used in the merge process.
Thus, the final answer is:
- Time complexity: O(n log n)
- Space complexity: O(n)
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