Benchmark: Math.random to invs Date.now

Tests:

Math.random
Math.floor(Math.random() * 9999)
Date.now
Date.now()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.random
Date.now

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**What is being tested?**

The test is designed to compare two approaches for generating unique keys:

1. `Date.now()`: This method returns the number of milliseconds since the Unix epoch (January 1, 1970).
2. `Math.random() * 9999` (in a later benchmark): This method generates a random float between 0 and 1 and multiplies it by 9999.

**Options compared**

In this specific test case, there are only two options being compared: `Date.now()` and `Math.random()`. The goal is to determine which approach is better for generating unique keys.

**Pros and Cons of each approach**

1. **`Date.now()`**:
	* Pros:
		+ Fast execution (native function)
		+ Low overhead
		+ Can generate unique values within a specific range
	* Cons:
		+ May not be suitable for cryptographic purposes due to the limited range and potential collisions
2. **`Math.random() * 9999`**:
	* Pros:
		+ Suitable for cryptographic purposes due to the large range (0 to 9999)
		+ Can generate truly unique values within a specific range
	* Cons:
		+ Slower execution compared to `Date.now()` due to the additional multiplication operation
		+ May have higher overhead

**Library and special JS feature**

In this test case, no libraries are used. However, it's worth noting that `Date.now()` uses the browser's internal clock, which may not be perfectly synchronized with the system time.

**Other considerations**

When generating unique keys, it's essential to consider factors like:

* Uniqueness: Can the generated value ensure uniqueness within a specific range?
* Performance: How fast is the generation process?
* Security: Are the generated values suitable for cryptographic purposes?

**Alternatives**

If you need to generate truly unique keys, you might consider using:

1. **Cryptographically secure pseudo-random number generators (CSPRNGs)**: These libraries provide a way to generate cryptographically secure random numbers.
2. **UUID libraries**: Universally Unique Identifiers (UUIDs) are designed to generate unique identifiers.

Keep in mind that these alternatives may have additional dependencies and requirements, so be sure to evaluate them based on your specific use case.

In conclusion, the provided benchmark helps compare two approaches for generating unique keys: `Date.now()` and `Math.random() * 9999`. While `Date.now()` is fast and suitable for many use cases, `Math.random() * 9999` provides a larger range and is more suitable for cryptographic purposes. When choosing an approach, consider factors like uniqueness, performance, and security to select the best method for your specific requirements.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.61 Safari/537.36

Browser/OS: Chrome 102 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Math.random	4258579.5 Ops/sec
Date.now	5228650.5 Ops/sec

Related benchmarks:

Math.random to invs Date.now (version: 0)

Which is best for generating a unique key?

Comparing performance of: Math.random vs Date.now

Created: 2 years ago by: Guest

Jump to the latest result

Math.random

Date.now

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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