Benchmark: slice vs filter2

Script Preparation code:

var test=Array.from({length: 100000},() => Math.random())

Tests:

slice
[...test.slice(0,50),...test.slice(51)]
filter
test.filter((e,i)=>i!=50)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
filter

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 break down the benchmark and analyze what's being tested.

**Benchmark Overview**

The benchmark compares two approaches to slice an array of 100,000 random numbers: using the `Array.prototype.slice()` method and using the `Array.prototype.filter()` method with a custom callback function. The goal is to determine which approach performs better.

**Approaches Compared**

1. **`Array.prototype.slice()`**: This method creates a new array containing a subset of elements from the original array, starting at the specified index (in this case, 0) and ending at the specified end index (also 50). The pros of this approach are:
	* Simple and well-known API.
	* Fast, as it only requires indexing into the original array.
	* Can be used with other methods, such as `concat()` or `spread()`.
However, the cons are:
	* Creates a new array, which can lead to memory allocation overhead.
	* Does not modify the original array.
2. **`Array.prototype.filter()`**: This method creates a new array containing only elements from the original array that pass the specified test (in this case, `i != 50`). The pros of this approach are:
	* Also simple and well-known API.
	* Can be used with other methods, such as `map()` or `reduce()`.
However, the cons are:
	* Creates a new array, which can lead to memory allocation overhead.
	* May require more CPU cycles to execute, depending on the callback function.

**Other Considerations**

Both approaches have similar performance characteristics in terms of time complexity (O(n)), where n is the number of elements being sliced/filtering. However, the `filter()` approach may be slightly slower due to the additional overhead of executing the callback function for each element.

**Library Used**

The benchmark uses no external libraries beyond what's built into JavaScript and its implementations in the two tested methods (`Array.prototype.slice()` and `Array.prototype.filter()`).

**Special JS Feature or Syntax**

There is no special JavaScript feature or syntax used in this benchmark. It only relies on standard ECMAScript features.

**Other Alternatives**

If you wanted to test a different approach, some alternatives could be:

* Using the `Array.prototype.indexOf()` method to find the index of the first element that matches the condition and then using `slice()` with two arguments.
* Using a loop to manually iterate over the elements and check for the condition.
* Using a library like Lodash's `filter` function.

In summary, the benchmark compares the performance of two approaches: slicing an array using `Array.prototype.slice()` versus filtering an array using `Array.prototype.filter()`. Both methods have similar performance characteristics, but the `filter()` approach may be slightly slower due to additional CPU overhead.

Related benchmarks:

slice vs filter2 (version: 0)

Comparing performance of: slice vs filter

Created: 5 years ago by: Guest

Jump to the latest result

slice

filter

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):