Learn Bubble Sort - Interactive Learning
Master Bubble Sort - DSA Learning Platform 🫧 Bubble Sort Beginner O(n²) Learn the simplest sorting algorithm - watch elements bubble up to their correct positions 📖 Understanding Bubble Sort Concept Algorithm Complexity Use Cases What is Bubble Sort? Bubble Sort is the simplest sorting algorithm that works by repeatedly swapping adjacent elements if they are in the wrong order. The algorithm gets its name because smaller elements "bubble" to the top of the list. In each pass through the array, the largest unsorted element moves to its correct position at the end, like a bubble rising to the surface. 🔑 Key Characteristics Simplest sorting algorithm to understand In-place algorithm (O(1) extra space) Stable sort (preserves order of equal elements) Adaptive - can detect if array is sorted Good for educational purposes Bubble Rising Analogy Pass 1: [5, 1, 4, 2, 8] → swap [1, 5, 4, 2, 8] → swap [1, 4, 5, 2, 8] → swap [1, 4, 2, 5, 8] → no swap [1, 4, 2, 5, 8] ← 8 is sorted! Pass 2: [1, 4, 2, 5, 8] → no swap [1, 4, 2, 5, 8] → swap [1, 2, 4, 5, 8] → no swap [1, 2, 4, 5, 8] ← 5 is sorted! Pass 3: [1, 2, 4, 5, 8] → no swaps! Array is sorted! ✓ Algorithm Steps 1. Compare adjacent elements: Start from the beginning of the array. 2. Swap if needed: If the left element is greater than the right, swap them. 3. Move forward: Move to the next pair of adjacent elements. 4. Repeat passes: After each pass, the largest unsorted element is in place. 5. Optimize: If no swaps in a pass, array is sorted - stop early! Pseudocode procedure bubbleSort(A: array) n = length(A) for i = 0 to n-1 do swapped = false for j = 0 to n-i-2 do if A[j] > A[j+1] then swap(A[j], A[j+1]) swapped = true end if end for // Early exit if no swaps if not swapped then break end if end for end procedure Time & Space Complexity ⏱️ Time Complexity Best Case: O(n) - Already sorted (with optimization) Average Case: O(n²) - Random order Worst Case: O(n²) - Reverse sorted 💾 Space Complexity O(1) - Only uses constant extra space In-place sorting algorithm Why O(n) Best Case? Already Sorted: [1, 2, 3, 4, 5] Pass 1: Compare all adjacent pairs No swaps needed! swapped = false Exit early! Only n-1 comparisons made. Time = O(n) when array is already sorted This optimization makes Bubble Sort "adaptive" - it can detect sorted data When to Use Bubble Sort? ✅ Good For Educational purposes - understanding sorting Very small datasets Nearly sorted data (with optimization) When simplicity is more important than speed Detecting if data is already sorted ❌ Not Recommended For Large datasets Performance-critical applications Real-world production code Random data (use Quick Sort or Merge Sort) Comparison with Other Sorts Algorithm Best Average Worst Stable ───────────────────────────────────────────────── Bubble Sort O(n) O(n²) O(n²) Yes Selection Sort O(n²) O(n²) O(n²) No Insertion Sort O(n) O(n²) O(n²) Yes Quick Sort O(nlogn) O(nlogn) O(n²) No Merge Sort O(nlogn) O(nlogn) O(nlogn) Yes Bubble Sort: Simple but...
Subject: Data Structures with Animation | Chapter: Sorting Algorithms with Animation