🧮 Sorting Problems
Welcome to the Sorting section of JDCodebase!
Sorting is a core concept in computer science and often appears in real-world tasks like data processing, searching, and optimization. Understanding different sorting techniques helps in writing efficient and elegant code.
🔧 Basic Approach
- Choose the right sorting technique based on time and space needs.
- Sort the array in-place if possible, unless stability or extra copies are required.
- Combine sorting with other techniques like binary search, two pointers, or greedy logic.
📚 Common Sorting Techniques
- Bubble Sort: Repeatedly swaps adjacent elements. Easy to understand but slow (O(n²)).
- Selection Sort: Repeatedly selects the minimum and moves it to the front. Also O(n²).
- Insertion Sort: Builds the final sorted array one element at a time. Great for small or nearly sorted arrays.
- Merge Sort: Divide and conquer approach that splits the array and merges it back sorted. Stable and guaranteed O(n log n).
- Quick Sort: Picks a pivot, partitions the array around it. Fast in practice (avg. O(n log n)), but worst-case O(n²).
- Counting Sort: Non-comparison sort. Best for sorting integers in a limited range in O(n + k) time.
- Built-in JavaScript Sort: Use
.sort((a, b) => a - b)for numeric sort. Behind the scenes, it uses quicksort (V8 engine).