JavaScript’s math random function is incredibly handy for generating random numbers, but it’s also surprisingly easy to misuse. Many developers, especially beginners, make mistakes that can lead to biased results, unexpected behavior, or even security issues. Understanding these pitfalls can save you time and headaches.

One of the most common mistakes is incorrectly scaling the output. math random generates a floating-point number between 0 (inclusive) and 1 (exclusive). If you want a random integer within a specific range, say 1 to 10, a simple multiplication alone won’t suffice—you must also use Math.floor() or Math.ceil() carefully. Off-by-one errors here are very common. For example, using Math.floor(Math.random() * 10) gives 0–9, not 1–10, which can cause subtle bugs in your application.

Another frequent issue is assuming true randomness. math random is a pseudo-random number generator (PRNG), meaning it follows an algorithm and is deterministic under the hood. For most applications, this is fine, but it’s not suitable for cryptographic purposes, generating secure tokens, or password handling. For those cases, alternatives like crypto.getRandomValues() are safer.

Developers also sometimes reuse math random results in ways that introduce bias, like improperly shuffling arrays or generating weighted probabilities without adjusting the formula. Using a proper algorithm, such as the Fisher-Yates shuffle, avoids these biases.

Testing and debugging random behavior can also be tricky. Tools like Keploy can help here by capturing API traffic and simulating realistic scenarios, allowing you to test how random number logic performs under real-world conditions.

The key to avoiding mistakes with math random is understanding its limitations, scaling it correctly, and using appropriate tools when randomness affects critical functionality. With careful use, math random remains a versatile and reliable tool for JavaScript developers.