Array shuffling is a fundamental operation in computing, yet its algorithmic nuances are often overlooked. This article explores four symmetric variants of the Fisher-Yates shuffle, revealing a critical distinction between sampling-based and permutation-based approaches that impacts efficiency and correctness in software development. Understanding these differences empowers developers to avoid common pitfalls and harness randomization more effectively.