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| 1 | +# 📘 Divide and Conquer (Folder 15) |
| 2 | + |
| 3 | +## 🧠 Overview |
| 4 | +Divide and Conquer is a problem-solving paradigm where a problem is: |
| 5 | +1. Divided into smaller subproblems |
| 6 | +2. Solved recursively |
| 7 | +3. Combined to get the final result |
| 8 | + |
| 9 | +This approach is efficient for sorting, searching, and optimization problems. |
| 10 | + |
| 11 | +--- |
| 12 | + |
| 13 | +## 📌 Topics Covered |
| 14 | + |
| 15 | +### 🔹 Sorting Algorithms |
| 16 | +- Merge Sort (Basic Implementation) |
| 17 | +- Merge Sort (Space Optimized) |
| 18 | +- Quick Sort |
| 19 | + |
| 20 | +### 🔹 Searching Technique |
| 21 | +- Search in Sorted and Rotated Array |
| 22 | + |
| 23 | +### 🔹 Analysis |
| 24 | +- Worst Case Analysis of Quick Sort |
| 25 | + |
| 26 | +### 🔹 Practice Problems |
| 27 | +- Additional problems |
| 28 | + |
| 29 | +--- |
| 30 | + |
| 31 | +## ⚡ Time & Space Complexity |
| 32 | + |
| 33 | +| Algorithm | Best Case | Average Case | Worst Case | Space Complexity | |
| 34 | +|------------|------------|-------------|-------------|------------------| |
| 35 | +| Merge Sort | O(n log n) | O(n log n) | O(n log n) | O(n) | |
| 36 | +| Quick Sort | O(n log n) | O(n log n) | O(n^2) | O(log n) | |
| 37 | + |
| 38 | +--- |
| 39 | + |
| 40 | +## 🔍 Key Concepts |
| 41 | + |
| 42 | +### ✅ Merge Sort |
| 43 | +- Stable sorting algorithm |
| 44 | +- Uses extra space for merging |
| 45 | +- Guaranteed O(n log n) performance |
| 46 | + |
| 47 | +### ✅ Quick Sort |
| 48 | +- In-place sorting algorithm |
| 49 | +- Faster in practice |
| 50 | +- Performance depends on pivot selection |
| 51 | + |
| 52 | +### ⚠️ Worst Case in Quick Sort |
| 53 | +Occurs when: |
| 54 | +- Array is already sorted |
| 55 | +- Pivot is always smallest or largest |
| 56 | + |
| 57 | +Result: |
| 58 | +- Time Complexity becomes O(n^2) |
| 59 | + |
| 60 | +Optimization: |
| 61 | +- Random pivot |
| 62 | +- Median-of-three |
| 63 | + |
| 64 | +--- |
| 65 | + |
| 66 | +## 🔁 Search in Rotated Sorted Array |
| 67 | +- Uses modified binary search |
| 68 | +- One half of the array is always sorted |
| 69 | +- Time Complexity: O(log n) |
| 70 | + |
| 71 | +--- |
| 72 | + |
| 73 | +## 🧪 Practice Focus |
| 74 | +- Strengthen recursion + divide and conquer thinking |
| 75 | +- Improve problem-solving skills |
| 76 | +- Understand optimization techniques |
| 77 | + |
| 78 | +--- |
| 79 | + |
| 80 | +## 🚨 Important Notes |
| 81 | +- Merge Sort is stable, Quick Sort is not |
| 82 | +- Merge Sort uses extra memory, Quick Sort is in-place |
| 83 | +- Algorithm choice depends on constraints |
| 84 | + |
| 85 | +--- |
| 86 | + |
| 87 | +## 📂 File Structure |
| 88 | + |
| 89 | +``` |
| 90 | +15_divide_and_conquer/ |
| 91 | +├── MergeSortBasic.java |
| 92 | +├── MergeSortOptimized.java |
| 93 | +├── QuickSort.java |
| 94 | +├── SearchInRotatedSortedArray.java |
| 95 | +├── PracticeProblems.java |
| 96 | +└── README.md |
| 97 | +``` |
| 98 | + |
| 99 | +--- |
| 100 | + |
| 101 | +## 🎯 Goal |
| 102 | +- Build strong understanding of Divide and Conquer |
| 103 | +- Write clean and optimized code |
| 104 | +- Prepare for interview-level problems |
| 105 | + |
| 106 | +--- |
| 107 | + |
| 108 | +## 📌 Final Takeaway |
| 109 | +Divide and Conquer is about breaking complex problems into smaller parts and solving them efficiently. |
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