Quick Sort is a popular and efficient sorting algorithm that uses a “divide and conquer” approach. It works by selecting a ‘pivot’ element and rearranging the array so that elements smaller than the pivot come before it, and elements larger come after it. This process is then applied recursively to the smaller sub-arrays. In previous articles, we’ve discussed the theory behind Quick Sort, its partitioning step, and its implementation. Now, let’s bring this algorithm to life with visualizations and animations!
Key Concepts of Quick Sort Algorithm
Before we dive into vizualizations, let’s review the main ideas behind quick sort in simple terms:
- Divide and Conquer: Quick sort solves the big problem by breaking it into smaller, more manageable pieces.
- Pivot Selection: We choose one element (called the “pivot”) from the array as a reference point.
- Partitioning: We rearrange the array around the pivot so that:
- Smaller elements than pivot go to the left of the pivot
- Larger elements than pivot go to the right of the pivot
- After this step, the pivot is exactly where it would be in the final sorted array
- Recursion: We repeat the same process on the left and right portions of the array (the smaller pieces).
- Stopping Point: We stop dividing when we reach portions with zero or one element, as these are already sorted by definition.
Think of it like organizing books on a shelf - you pick one book as a reference, put shorter books to the left, taller books to the right, and then repeat the process for each group until everything is in order.
Visualization of Array Partitioning
Partitioning is the heart of the Quick Sort algorithm. In this step, we choose a ‘pivot’ element from the array. The goal is to rearrange the array (or a part of it) so that all elements smaller than the pivot end up on one side, and all elements greater than the pivot end up on the other side. The pivot itself ends up in its final sorted position for this pass. The visualization below demonstrates this process step-by-step, showing how elements swap places relative to the chosen pivot.
Visualization of Recursive Quick Sort Algorithm
After the first partitioning step, the array is divided into two smaller sub-arrays (one with elements smaller than the pivot, one with elements larger). Quick Sort then applies the same partitioning logic recursively to these sub-arrays. This “divide and conquer” strategy continues until the sub-arrays are so small (usually just one element) that they are inherently sorted. The visualization below illustrates this entire recursive process, showing how the array is broken down and sorted piece by piece.
What’s Next?
Now that you’ve visualized how Quick Sort works, you might want to explore:
- Quick Sort Algorithm: Time and Space Complexity Analysis to understand its efficiency in terms of
timeandmemory. - Different Pivot Selection Strategies in Quick Sort and how the choice of pivot impacts performance.
- Optimizations for Quick Sort Algorithm to make it even faster in certain situations.
- Advantages and Disadvantages of Quick Sort Algorithm to know when it’s the best choice.
- Common Mistakes in Quick Sort Implementation and how to avoid them when writing code.