



How can you explain the concept of time complexity using bubble sort as an example?
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what is bubble sort algorithm
- How might a functional language approach the implementation of a sorting algorithm like bubble sort?
- How do you count the number of comparisons and swaps performed by bubble sort as a function of the input size n?
- Why is bubble sort considered a space-efficient algorithm?
- Explain what O(n^2) time complexity means in the context of bubble sort.
- How does the lack of random access in linked lists affect the implementation and performance of bubble sort?
- How does the limited range of values benefit counting sort or radix sort more than bubble sort?
- Can you use bubble sort to detect if a list is already sorted?
- What strategies can be used to reduce the number of comparisons in sorting algorithms when the comparison operation is costly (e.g., caching comparison results)?
- Are there any niche applications or specific constraints where bubble sort might still be a practical choice?
- Can the number of passes in bubble sort ever be less than n-1 for a list of n elements?
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