Quick Sort remains a staple in computer science, prized for its speed and elegance. The article walks readers from a simple functional implementation to in‑place variants, highlighting the Lomuto and Hoare partition schemes that power most production systems. It explains the divide‑and‑conquer core: pick a pivot, split the array, and recurse.

Functional Quick Sort is easy to read but consumes extra memory; in‑place versions swap elements in place, reducing space to O(log n). It also contrasts Lomuto’s pivot‑final placement with Hoare’s boundary‑based approach, noting that Hoare typically performs fewer swaps and handles duplicates better. It also reviews time complexities—best and average O(n log n), worst O(n²) when the pivot choice is poor—and space costs for each variant.

For developers, the article offers ready‑to‑copy JavaScript snippets and a side‑by‑side comparison table. Understanding these nuances helps when choosing an algorithm for interview questions or real‑world sorting tasks. These insights also clarify why many interviewers favor Quick Sort over simpler algorithms like Bubble Sort, given its average‑case efficiency.