Benchmark: Math.random vs crypto.getRandom Alberto

Tests:

Math.random()
Math.floor(Math.random() * 4294967296);
crypto.getRandomValues()
crypto.getRandomValues(new Uint32Array(1))[0]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.random()
crypto.getRandomValues()

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 18_2 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) FxiOS/133.0 Mobile/15E148 Safari/605.1.15

Browser/OS: Mobile Safari 18 on iOS 18.2

View result in a separate tab

Test name	Executions per second
Math.random()	326548352.0 Ops/sec
crypto.getRandomValues()	3739616.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**What is being tested?**

The provided JSON benchmark defines two individual test cases:

1. `Math.random()`: This test case measures the performance of the built-in `Math.random()` function, which generates a random number between 0 (inclusive) and 1 (exclusive).
2. `crypto.getRandomValues()`: This test case measures the performance of the `crypto.getRandomValues()` function, which generates cryptographically secure random numbers.

**Options compared**

The two options being compared are:

* **Math.random()**: A built-in JavaScript function that uses a pseudo-random number generator to generate random numbers.
* **crypto.getRandomValues()**: A Web Cryptography API (W3C) function that generates cryptographically secure random numbers.

**Pros and cons of each approach:**

1. **Math.random():**
	* Pros:
		+ Easy to implement and understand.
		+ Works on most browsers and platforms.
	* Cons:
		+ Pseudo-random, which means it's not suitable for applications that require true randomness (e.g., cryptographic purposes).
		+ May generate predictable patterns or sequences if used in a loop with the same seed value.
2. **crypto.getRandomValues():**
	* Pros:
		+ Generates truly random numbers, making it suitable for cryptographic purposes.
		+ Provides better entropy and randomness compared to `Math.random()`.
	* Cons:
		+ Requires support for Web Cryptography API (W3C) in browsers or platforms.
		+ May be slower than `Math.random()` due to the additional cryptographic overhead.

**Other considerations:**

* **Libraries:** In the provided benchmark, neither test case uses a specific library. However, if a test case were to use a library like `Cryptico` or `random-js`, it would provide an alternative implementation of `crypto.getRandomValues()`.
* **Special JS features or syntax:** Neither test case uses any special JavaScript features or syntax beyond the built-in functions and APIs.
* **Alternatives:**
	+ For non-cryptographic purposes, other alternatives to `Math.random()` might include:
		- `Number.seedrandom()`: A library function that generates random numbers using a seed value.
		- `randint():` A function from libraries like `crypto-js` or `seedrandom`.
	+ For cryptographic purposes, alternative implementations of `crypto.getRandomValues()` might include:
		- `window.crypto.getRandomValues()`: Another W3C API for generating cryptographically secure random numbers.
		- `Math.random()` with a different seed value (not recommended due to predictability concerns).

In summary, the provided benchmark compares the performance of two JavaScript functions: `Math.random()` and `crypto.getRandomValues()`. While `Math.random()` is easy to implement and suitable for non-cryptographic purposes, `crypto.getRandomValues()` provides better randomness and entropy, making it a more suitable choice for cryptographic applications.

Related benchmarks:

Math.random vs crypto.getRandom Alberto (version: 0)

Comparing performance of: Math.random() vs crypto.getRandomValues()

Created: 4 years ago by: Guest

Jump to the latest result

Math.random()

crypto.getRandomValues()

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):