Benchmark: slice vs filter (10000000)

Script Preparation code:

var test=Array.from({length: 10000000},()=>Math.random())

Tests:

slice
test.slice(0, 4)
filter
test.filter((e,i)=>i!=4)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
filter

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 3 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and its implications.

**What is being tested?**

The provided JSON represents two test cases: `slice` and `filter`. These functions are part of the JavaScript Array prototype, which allows you to manipulate arrays in various ways. The benchmark tests these two functions on a large array (`10000000`) with random elements.

**Options compared**

In this benchmark, the two options being compared are:

1. `slice`: This function returns a new array containing the elements of the original array, starting from index 0 and taking a specified number of elements (in this case, 4).
2. `filter`: This function creates a new array with all elements that pass a provided test.

**Pros and Cons of each approach**

* **Slice:**
	+ Pros:
		- Returns a new array without modifying the original.
		- Can be faster for smaller arrays since it doesn't require iterating over the entire array to determine which elements are included.
	+ Cons:
		- Returns only 4 elements, even though the input array has 10000000 elements. This might lead to inefficient use of resources and high memory usage.
* **Filter:**
	+ Pros:
		- Only includes elements that meet the condition, potentially reducing memory usage.
	+ Cons:
		- Can be slower since it requires iterating over the entire array to determine which elements are included.

**Library**

There is no external library used in this benchmark. Both `slice` and `filter` are built-in JavaScript functions.

**Special JS feature or syntax**

None of the test cases use any special JavaScript features or syntax.

**Other alternatives**

If you're interested in optimizing array manipulation, here are some alternative approaches:

1. **Array.prototype.map()**: Instead of using `slice()` or `filter()`, consider using `map()` to create a new array with transformed elements.
2. **Array.prototype.reduce()**: Use `reduce()` to accumulate the elements that meet the condition, instead of using `filter()`.

Keep in mind that the performance differences between these approaches can be significant, and the choice ultimately depends on your specific use case and requirements.

The benchmark's results will help you determine which approach is faster for your particular scenario.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.5005.61 Safari/537.36

Browser/OS: Chrome 102 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
slice	10579480.0 Ops/sec
filter	3.5 Ops/sec

Related benchmarks:

slice vs filter (10000000) (version: 7)

Comparing performance of: slice vs filter

Created: 2 years ago by: Registered User

Jump to the latest result

slice

filter

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Sumamry (model llama3.2:3b, generated 3 days ago):