Benchmark: Slice & Splice vs ES6 Array Spread

Script Preparation code:

var array = Array.from({ length: 100 }).map((val, i) => i);

Tests:

Slice & Splice
var messages = array.slice().splice(38, 1);
ES6 Array Creation
var messages = [...array].splice(38, 1);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Slice & Splice
ES6 Array Creation

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 7 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36

Browser/OS: Chrome 125 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Slice & Splice	10704300.0 Ops/sec
ES6 Array Creation	10654868.0 Ops/sec

Autogenerated LLM Summary (model llama3.1:latest, generated 2 months ago):

LLMs can make mistakes. Check important info.

Let's dive into the benchmark test cases.

**Benchmark Overview**

The provided JSON represents a benchmark test case that compares two different methods of modifying an array in JavaScript: `Slice & Splice` and `ES6 Array Spread`.

**Test Case 1: Slice & Splice**

This test case uses the traditional `slice()` and `splice()` methods to modify the array.

* The "Benchmark Definition" code creates a new array `messages` by calling `array.slice()` followed by `array.splice(38, 1)`. This essentially removes the element at index 38 from the original array.
* In this approach, two separate operations are performed: first, creating a shallow copy of the original array using `slice()`, and then modifying the copied array using `splice()`.

**Pros and Cons**

The traditional `Slice & Splice` method has some advantages:

* It's well-supported in older browsers and JavaScript engines.
* The code is simple to understand and maintain.

However, it also has some drawbacks:

* Creating a shallow copy of the original array using `slice()` can be computationally expensive for large arrays.
* The use of `splice()` can lead to unexpected behavior if not carefully managed.

**Test Case 2: ES6 Array Spread**

This test case uses the modern `ES6 Array Spread` feature to create a new array and then modify it using `splice()`.

* In this approach, a new array is created using the spread syntax `[...array]`, which creates a shallow copy of the original array.
* The resulting array is then modified using `array.splice(38, 1)`.

**Pros and Cons**

The ES6 Array Spread method has some benefits:

* It's more concise and expressive than the traditional `Slice & Splice` approach.
* The spread syntax can be used to create a new array with the desired properties, making it easier to reason about the code.

However, it also has some drawbacks:

* This feature is not supported in older browsers or JavaScript engines that don't implement ES6 features.
* The syntax might be unfamiliar to developers who are not up-to-date with modern JavaScript.

**Library**

No external library is used in these test cases.

**Special JS Feature or Syntax**

The `ES6 Array Spread` method uses the spread syntax `[...array]`, which is a special feature introduced in ECMAScript 2015 (ES6). This syntax allows creating a new array by spreading the elements of an existing array.

**Alternatives**

Other alternatives for modifying arrays include:

* Using `filter()`, `map()`, or `reduce()` methods to create a new array with the desired properties.
* Employing third-party libraries like Lodash or Underscore.js, which provide additional utility functions for working with arrays and other data structures.

These alternatives might offer better performance, readability, or maintainability depending on the specific use case. However, they may also introduce additional dependencies and complexity.

Related benchmarks:

Slice & Splice vs ES6 Array Spread (version: 2)

Comparing performance of: Slice & Splice vs ES6 Array Creation

Created: 6 years ago by: Registered User

Jump to the latest result

Slice & Splice

ES6 Array Creation

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.1:latest, generated 2 months ago):