Efficient Adaptive Sorting Algorithm for Floating-Point Numbers in JavaScript: Outperforming Existing Solutions

Introduction: The Sorting Dilemma in JavaScript Sorting is a deceptively simple problem. At its core, it’s about arranging data in a specific order. But in JavaScript, particularly with floating-point numbers, this simplicity unravels into a complex web of inefficiencies. Why? Because JavaScript’s native Array.sort() is a generalist—it’s designed to handle any data type, but this flexibility comes at a cost. For floating-point numbers, it defaults to a comparison-based approach, which is inherently slow due to the nature of IEEE 754 floating-point arithmetic. Each comparison involves costly operations like handling special values (NaN, ±0, ±Infinity), dealing with precision loss, and managing edge cases like denormalized numbers. The result? A sorting process that heats up your CPU cycles and expands execution time unnecessarily. Enter ayoob-sort , an adaptive sorting engine that challenges this status quo. Its innovation lies in two key mechanisms: adaptive algorithm selection and a n