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You’ve learned bubble sort. Let’s see how well you understand it.
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Question 1: What is the worst-case time complexity of bubble sort? A. O(n) B. O(n log n) C. O(n²) (Correct) D. O(2ⁿ) Explanation: Bubble sort has O(n²) worst-case time complexity because it uses nested loops, each potentially iterating n times.
Question 2: Why is bubble sort called "bubble" sort? A. It creates bubbles in memory B. Larger elements bubble up to the end (Correct) C. It uses bubble data structures D. It was invented by someone named Bubble Explanation: Bubble sort gets its name because larger elements "bubble up" to their correct position at the end of the array, like bubbles rising in water.
Question 3: What is the space complexity of bubble sort? A. O(n) B. O(n log n) C. O(1) (Correct) D. O(log n) Explanation: Bubble sort has O(1) space complexity because it only uses a constant amount of extra space for variables, sorting in-place.
Question 4: With early termination optimization, what is the best-case time complexity? A. O(n²) B. O(n log n) C. O(n) (Correct) D. O(1) Explanation: With early termination, if the array is already sorted, bubble sort only needs one pass through the array, giving O(n) best-case complexity.
Question 5: In bubble sort, after the first pass, what can we say about the last element? A. It is the smallest B. It is the largest (Correct) C. It is in a random position D. Nothing can be said Explanation: After the first pass, the largest element has "bubbled up" to the last position, so we know it is in its correct sorted position.
Implement bubble sort with early termination:
Run code to see output...
You’ve mastered:
✅ Bubble Sort Algorithm : Compare adjacent, swap if needed, repeat
✅ Implementation : Nested loops with swap logic
✅ Complexity : O(n²) time, O(1) space
✅ Optimization : Early termination for best case O(n)
✅ When to Use : Educational purposes, not production
With bubble sort knowledge, you can:
Understand sorting fundamentals
Implement simple sorting in small projects
Appreciate why better algorithms exist
Build intuition for algorithm analysis
Solve basic sorting problems
Practice with more sorting problems
Learn faster algorithms (quicksort, mergesort)
Study algorithm analysis techniques
Explore other O(n²) sorting algorithms
Great job completing this tutorial!