


What assumptions are typically made when analyzing the average-case performance of sorting algorithms?
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what is bubble sort algorithm
- How does the size of the input affect the performance of bubble sort?
- Why is bubble sort still taught despite its lower efficiency compared to other algorithms?
- 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?
- How does the number of swaps in insertion sort and selection sort compare to bubble sort?
- Are there any precision issues to consider when sorting floating-point numbers using bubble sort?
- Under what conditions would bubble sort perform the maximum number of swaps?
- Consider sorting data that is too large to fit into main memory. How would bubble sort perform in an external sorting scenario?
- How does the number of comparisons in bubble sort relate to its energy usage?
- Consider the visualization of the optimized bubble sort. How does the early termination condition manifest in the visual representation?
- One common misconception is that bubble sort is always the simplest algorithm to implement. Why might this not always be true?
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