Benchmark: JavaScript spread vs slice vs for

Script Preparation code:

const ITERATIONS = 500000;
var index = ITERATIONS/2;
var n = Math.random();

var list = [];
for (let i = 0; i < length; i += 1) {
  list.push(Math.random());
}

Tests:

Array clone: spread operator
const clone = [...list];
Array clone: slice
const clone = list.slice();
Array Clone: for loop
const clone = []; for (let i=0;i<list.length;i++) { clone[i] = list[i]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array clone: spread operator
Array clone: slice
Array Clone: for loop

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The benchmark measures the performance of three approaches to clone an array in JavaScript:

1. Using the spread operator (`[...]`).
2. Using the `slice()` method.
3. Using a traditional `for` loop to iterate over the elements and assign them to a new array.

**Options Comparison**

Here's a brief comparison of the three options, their pros and cons, and other considerations:

1. **Spread Operator (`[...]`)**:
	* Pros: concise, readable, and efficient.
	* Cons: requires modern JavaScript support (ES6+).
	* Considerations: The spread operator creates a shallow copy of the array, which can be beneficial if you're working with objects that contain arrays as values. However, it may not be suitable for deep cloning or modifying the original array.
2. **`slice()` Method**:
	* Pros: widely supported across browsers and environments, efficient, and easy to use.
	* Cons: creates a shallow copy of the array.
	* Considerations: The `slice()` method is part of the ECMAScript standard, ensuring compatibility with most modern browsers and environments. However, it may not be suitable for deep cloning or modifying the original array.
3. **Traditional `for` Loop**:
	* Pros: language-agnostic, no special libraries or features required.
	* Cons: verbose, error-prone, and less efficient than the other two options.
	* Considerations: The traditional `for` loop is a fundamental construct in JavaScript, making it easy to implement and understand. However, it can be time-consuming to write and maintain.

**Library and Special Features**

In this benchmark, no libraries are used beyond the built-in JavaScript functions and data structures. There are no special features or syntax being tested.

**Other Alternatives**

For array cloning, you may also consider using other approaches, such as:

1. `Array.prototype.slice.call()`
2. `Array.prototype.slice.apply()`
3. `Array.from()` (although this requires modern JavaScript support)
4. Third-party libraries like Lodash or Underscore.js

Keep in mind that the choice of approach depends on your specific use case, performance requirements, and compatibility constraints.

**Benchmark Result Interpretation**

The provided benchmark result shows the execution per second for each test case:

* **Array Clone: for loop**: 11680545.0 executions/second (Chrome 86, Desktop, Windows)
* **Array clone: slice**: 11057238.0 executions/second (Chrome 86, Desktop, Windows)
* **Array clone: spread operator**: 10444540.0 executions/second (Chrome 86, Desktop, Windows)

These results indicate that the traditional `for` loop is the fastest approach, followed closely by the `slice()` method. The spread operator is slightly slower.

Please note that these results are specific to Chrome 86 on a desktop device running Windows and may not be representative of other browsers, environments, or hardware configurations.

Related benchmarks:

JavaScript spread vs slice vs for (version: 0)

Comparing performance of: Array clone: spread operator vs Array clone: slice vs Array Clone: for loop

Created: 5 years ago by: Guest

Jump to the latest result

Array clone: spread operator

Array clone: slice

Array Clone: for loop

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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