Benchmark: concat vs spread 1

Script Preparation code:

var params = ['hello', true, 7];

Tests:

Array.prototype.concat
var other = [1, 2].concat(params);
spread operator
var other = [1, 2, ...params];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.prototype.concat
spread operator

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.122 Safari/537.36

Browser/OS: Chrome 81 on Mac OS X 10.15.5

View result in a separate tab

Test name	Executions per second
Array.prototype.concat	3996117.2 Ops/sec
spread operator	8951893.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Definition**

The provided JSON represents a benchmark definition for measuring the performance difference between two approaches: the traditional `concat()` method and the new ES6 spread operator (`...`).

**Script Preparation Code**
```javascript
var params = ['hello', true, 7];
```
This code defines an array `params` with three elements.

**Html Preparation Code**
The `Html Preparation Code` is null, indicating that no HTML code is needed for this benchmark.

**Individual Test Cases**

There are two test cases:

1. **Array.prototype.concat**: This test case uses the traditional `concat()` method to concatenate the `params` array with another array `[1, 2]`.
```javascript
var other = [1, 2].concat(params);
```
2. **spread operator**: This test case uses the new ES6 spread operator (`...`) to concatenate the `params` array with another array `[1, 2]`.
```javascript
var other = [1, 2, ...params];
```
**Pros and Cons of Different Approaches**

The main difference between these two approaches is how they handle arrays and performance. Here's a brief summary:

* **concat() method**:
	+ Pros: Widely supported, easy to implement, and compatible with older browsers.
	+ Cons: Creates a new array, which can lead to higher memory usage and slower performance for large datasets.
* **Spread operator (`...`)**:
	+ Pros: More efficient, as it uses a single assignment operation, and creates an iterator that can be used to process the elements of the original array without creating a new one.
	+ Cons: Requires modern JavaScript engines and browsers that support the spread operator.

**Library Usage**

There is no specific library mentioned in the benchmark definition. However, if you were to implement this benchmark in your own code, you might consider using libraries like `Benchmark.js` or `Fastify` for building benchmarks.

**Special JS Feature/Syntax**

The use of the new ES6 spread operator (`...`) requires modern JavaScript engines and browsers that support it. The `concat()` method is a more traditional approach that has been supported by JavaScript engines for much longer.

**Other Alternatives**

If you want to measure the performance difference between other approaches, here are some alternatives:

* Using `Array.prototype.push()`: This approach can be faster than concatenating arrays using `+` or `[...]`, as it avoids creating a new array and modifies the original one in place.
* Using `Array.prototype.slice()` with an offset: This approach can be faster than concatenating arrays, as it allows the engine to skip the unnecessary elements at the end of the array.

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

Related benchmarks:

concat vs spread 1 (version: 0)

Compare the new ES6 spread operator with the traditional concat() method

Comparing performance of: Array.prototype.concat vs spread operator

Created: 4 years ago by: Registered User

Jump to the latest result

Array.prototype.concat

spread operator

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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