Benchmark: splice + spread vs filter to remove one item at given index

Script Preparation code:

var users = [
	{ 'user': 'joey',  'age': 32 },
 	{ 'user': 'ross',    'age': 41 },
  	{ 'user': 'chandler', 'age': 39 },
    	{ 'user': 'chandler', 'age': 39 },
      	{ 'user': 'chandler', 'age': 39 },
    	{ 'user': 'chandler', 'age': 39 },
    	{ 'user': 'chandler', 'age': 39 },
    	{ 'user': 'chandler', 'age': 39 },
    	{ 'user': 'chandler', 'age': 39 },
    	{ 'user': 'chandler', 'age': 39 },

]

Tests:

Filter
const result = users.filter((item, index) => index !== 3);
Slice + spread
const result = [...users.slice(0, 3), ...users.slice(4)];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Filter
Slice + spread

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'll provide an explanation of the provided benchmark, its options, and pros/cons of each approach.

**Benchmark Definition**

The benchmark tests two ways to remove one item from an array: using `filter` or by slicing the array with the spread operator (`...`). The input array `users` contains 7 elements with duplicates. The goal is to create a new array that excludes the item at index 3 (the fourth element).

**Options Compared**

The two options being compared are:

1. **Filter**: Using the `filter()` method, which creates a new array by iterating over each element in the original array and selecting those for which the provided function returns true.
2. **Slice + spread**: Using `slice()` to extract a subset of elements from the original array and then spreading that subset into a new array using the spread operator (`...`).

**Pros/Cons of Each Approach**

### Filter

Pros:

* More concise and readable code
* Can be easily adapted for larger datasets by passing in a function that returns true or false
* Typically faster than slicing due to its ability to stop iterating as soon as it finds a match (avoiding unnecessary computations)

Cons:

* May create intermediate arrays, which can consume memory if the input array is large.
* Performance may degrade if the filtering function is complex or slow.

### Slice + spread

Pros:

* Creates a new array in-place without creating additional intermediate arrays, making it more memory-efficient for large datasets.
* Can be useful when you need to perform multiple operations on the same dataset (e.g., filtering and then mapping).

Cons:

* Less readable code due to the use of `slice()` and spreading operators
* Requires careful consideration of array bounds and indexing to avoid errors.

**Library Usage**

In this benchmark, no libraries are explicitly mentioned. However, if a library like Lodash were used, it might provide a `filter` or `removeAt` method that could be compared in the benchmark.

**Special JS Features/Syntax**

This benchmark does not use any special JavaScript features or syntax beyond the ones mentioned above (e.g., arrow functions, spread operator). It relies on standard JavaScript methods and array operations.

**Other Alternatives**

If you wanted to test other approaches, some alternative options could include:

* Using `map()` in combination with `slice()`: This would create a new array by mapping each element to itself (i.e., leaving the original array unchanged).
* Using a custom implementation of the "remove-at" operation: This might involve writing an iterative algorithm that removes elements from the array one by one.
* Using a library like Array.prototype.at or Array.prototype.deleteAll() if available: These methods provide more convenient ways to remove elements at specific indices.

However, these alternatives are not mentioned in the provided benchmark, and their performance would likely be different due to variations in implementation complexity, memory usage, and execution speed.

Latest run results:

Run details: (Test run date: 8 days ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Linux

View result in a separate tab

Test name	Executions per second
Filter	9050116.0 Ops/sec
Slice + spread	4285162.0 Ops/sec

Related benchmarks:

splice + spread vs filter to remove one item at given index (version: 0)

Remove one item from array and return a new array with filter or slice and spread operator

Comparing performance of: Filter vs Slice + spread

Created: 4 years ago by: Guest

Jump to the latest result

Filter

Slice + spread

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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