Benchmark: Array splice vs concat vs spread

Tests:

splice
var a = [ "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello" ]; var b = [ "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello" ]; var other = b.splice(0, 0, ...a);
concat
var a = [ "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello" ]; var b = [ "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello" ]; var other = b.concat(a);
spread
var a = [ "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello" ]; var b = [ "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello", "hello" ]; var other = [...a, ...b]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
splice
concat
spread

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark is designed to compare the performance of three different methods for merging two arrays:

1. `Array.splice()`
2. `Array.concat()`
3. `Spread Operator` (`...`)

**Method Comparison**

Each test case defines a scenario where an array `a` and another array `b` are created with identical elements. Then, the same operation is performed on both arrays to merge them into a new array.

Here's what's being compared:

* `splice()`: The `splice()` method modifies the original array `b` by removing the first element (index 0) and adding all elements from another array (`a`) at that position.
* `concat()`: The `concat()` method creates a new array by copying all elements from two arrays (`a` and `b`).
* `Spread Operator`: The spread operator (`...`) creates a new array by copying all elements from one or more arrays (`a` and/or `b`) and merging them into a single array.

**Pros and Cons of Each Approach**

1. `splice()`:
	* Pros: Modifies the original array, potentially reducing memory allocation.
	* Cons: Can be slow for large arrays due to the overhead of modifying the array.
2. `concat()`: 
	* Pros: Creates a new array without modifying the original one, which can be faster for large arrays.
	* Cons: Requires additional memory allocation and copying elements between arrays.
3. `Spread Operator` (`...`):
	* Pros: Fast and efficient, creates a new array without modifying the original one, and allows for merging multiple arrays into a single array.
	* Cons: Creates an intermediate array during concatenation, which can consume additional memory.

**Library Usage**

None of the provided benchmark definitions use any external libraries. However, some modern JavaScript engines might use internal libraries or optimizations that are not exposed in the code.

**Special JS Features/Syntax**

The spread operator (`...`) is a relatively new feature introduced in ECMAScript 2015 (ES6). It allows for creating new arrays by copying elements from existing arrays.

**Alternative Approaches**

1. `Array.prototype.slice()`: This method creates a shallow copy of an array, similar to the spread operator.
2. `Array.prototype.reduce()` or `Array.prototype.forEach()`: These methods can be used to merge two arrays into one, but they have different performance characteristics and use cases.

In summary, the benchmark compares three common methods for merging arrays in JavaScript: `splice()`, `concat()`, and the spread operator (`...`). Each approach has its pros and cons, and understanding these differences is essential for optimizing array operations in JavaScript.

Related benchmarks:

Array splice vs concat vs spread (version: 0)

Comparing performance of: splice vs concat vs spread

Created: 6 years ago by: Registered User

Jump to the latest result

splice

concat

spread

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):