


Why are predictable and bounded execution times often critical in real-time systems?
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what is bubble sort algorithm
- What are the key differences in the implementation of bubble sort in different programming paradigms (e.g., imperative vs. functional)?
- Consider the number of inversions in a list as a measure of its disorder. How does bubble sort reduce the number of inversions with each pass?
- Are there any algorithmic techniques that incorporate bubble sort as a subroutine?
- What are the practical implications of O(n^2) time complexity for large datasets?
- How does the number of swaps in insertion sort and selection sort compare to bubble sort?
- Under what conditions would bubble sort perform the maximum number of swaps?
- Why are more efficient algorithms generally preferred in competitive programming where time limits are strict?
- Consider the implementation of bubble sort using different programming language paradigms (e.g., object-oriented, procedural). Are there any notable differences or advantages to a particular paradigm?
- What happens if the inner loop of bubble sort goes out of bounds?
- What are some common techniques used for distributed sorting (e.g., map-reduce based approaches)?
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