Benchmark: shuffle array [dsng-manscaped]

Tests:

map sort map
const arr = Array.from({length: 10000}); function shuffle(arr) { return arr .map((name) => ({ name, randomValue: Math.random() })) .sort((a, b) => a.randomValue - b.randomValue) .map(({ name }) => name); } shuffle(arr)
Fisher-Yates
const arr = Array.from({length: 10000}); function shuffle(array) { let currentIndex = array.length; let randomIndex; while (currentIndex != 0) { randomIndex = Math.floor(Math.random() * currentIndex); currentIndex--; [array[currentIndex], array[randomIndex]] = [array[randomIndex], array[currentIndex]]; } return array; } shuffle(arr)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map sort map
Fisher-Yates

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 3 days ago):

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided benchmark is designed to measure the performance of JavaScript's array shuffling algorithms. Specifically, it tests two approaches:

1. **Using `Array.prototype.sort()` with a custom comparison function**: This approach uses the built-in `sort()` method and provides a custom comparison function to sort the array elements based on their random values.
2. **Fisher-Yates shuffle algorithm**: This is an in-place shuffling algorithm that rearranges the elements of the array without using additional data structures.

**Comparison Options**

The benchmark compares these two approaches, providing insight into which one performs better under different conditions.

**Pros and Cons**

* **Using `Array.prototype.sort()` with a custom comparison function**:
	+ Pros: Simple to implement, leverages built-in functionality.
	+ Cons: Sorts the array in ascending order, which may not be desirable for all use cases; can be slower than other algorithms due to its inherent O(n log n) complexity.
* **Fisher-Yates shuffle algorithm**:
	+ Pros: Efficient, with a time complexity of O(n); rearranges elements in-place, avoiding additional data structures; suitable for most shuffling needs.
	+ Cons: Requires more code and manual implementation effort.

**Library Usage**

In the benchmark, the `Array.from()` method is used to create an array from a specified length. This method is a part of the ECMAScript Standard Library and provides a convenient way to create arrays without using the traditional `new Array()` constructor.

**Special JavaScript Feature/Syntax**

There are no specific JavaScript features or syntaxes mentioned in this benchmark. However, it's worth noting that the use of template literals (e.g., `"map sort map"`) is a feature introduced in ECMAScript 2015 (ES6) for creating string templates.

**Alternative Approaches**

Other array shuffling algorithms can be used as alternatives to the Fisher-Yates algorithm:

* **Randomized shuffle using `Math.random()`**: This approach involves generating random indices and swapping elements based on those indices.
* **Lomuto shuffle**: A variation of the Fisher-Yates algorithm that is slightly faster and more efficient.

Keep in mind that these alternative algorithms may have different performance characteristics, and the choice of implementation depends on specific requirements and use cases.

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/100.0.4896.127 Safari/537.36 Edg/100.0.1185.44

Browser/OS: Chrome 100 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
map sort map	196.6 Ops/sec
Fisher-Yates	311.7 Ops/sec

Related benchmarks:

shuffle array [dsng-manscaped] (version: 1)

Comparing performance of: map sort map vs Fisher-Yates

Created: 2 years ago by: Registered User

Jump to the latest result

map sort map

Fisher-Yates

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 3 days ago):