Computer Science – 19.1 Algorithms | e-Consult
19.1 Algorithms (1 questions)
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Here's a table comparing Bubble Sort and Merge Sort:
| Algorithm | Time Complexity (Worst Case) | Space Complexity | Stability |
| Bubble Sort | O(n2) | O(1) | Yes |
| Merge Sort | O(n log n) | O(n) | Yes |
Why are these criteria important?
- Time Complexity: This is crucial for performance-critical applications. An algorithm with a lower time complexity will generally be faster, especially for large datasets. Choosing an algorithm with poor time complexity can lead to significant delays and scalability issues.
- Space Complexity: This is important when memory is limited. Algorithms with low space complexity are preferred in environments with restricted memory resources, such as embedded systems or mobile devices. High space complexity can lead to memory exhaustion and program crashes.
- Stability: A stable sorting algorithm preserves the relative order of equal elements. This can be important in certain applications where the original order of elements needs to be maintained. While not always a primary concern, stability can be a desirable feature.
By considering these criteria, developers can select the most appropriate sorting algorithm for a given task, balancing performance, memory usage, and other factors.