Benchmark: slice vs filter 2

Script Preparation code:

var test=Array.from({length: 10000},()=>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:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Windows

View result in a separate tab

Test name	Executions per second
slice	12248.7 Ops/sec
filter	15817.1 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases to explain what's being tested, compared, and their pros and cons.

**What is being tested?**

The benchmark measures the performance difference between two JavaScript methods: `slice` and `filter`. The tests are run on a large array of 10,000 random numbers generated by `Array.from()` with an optional callback function (not used in this case).

**Options compared:**

1. **`slice`**: This method creates a shallow copy of a portion of an array.
2. **`filter`**: This method creates a new array with all elements that pass the test implemented by the provided function.

**Pros and Cons:**

* **`slice`**:
	+ Pros:
		- Faster for large arrays since it only copies the necessary elements, avoiding the overhead of creating a new array.
		- Can be more efficient when working with sparse arrays or arrays where not all elements need to be accessed.
	+ Cons:
		- Can be less readable and maintainable due to its mutable nature (it modifies the original array).
		- May not be suitable for use cases where you want to preserve the original array's state.
* **`filter`**:
	+ Pros:
		- More readable and maintainable since it creates a new array, preserving the original array's state.
		- Can be more flexible when working with complex filtering conditions or transformations.
	+ Cons:
		- Generally slower than `slice` due to the overhead of creating a new array and iterating over the elements.

**Other considerations:**

* Both methods have their trade-offs in terms of performance, readability, and maintainability. The choice between them depends on the specific use case and requirements.
* In this benchmark, the test is likely focused on measuring the raw execution speed of these two methods rather than considering factors like memory allocation, garbage collection, or cache locality.

**Library usage:**

In the provided benchmark definition, `Array.from()` is used to generate a large array of random numbers. This function is part of the ECMAScript standard and is widely supported by most modern JavaScript engines. Its purpose is to create an array from an iterable object (in this case, an object with a `length` property).

**Special JS feature or syntax:**

There are no special features or syntax used in this benchmark that would require specific handling or interpretation.

**Other alternatives:**

If you wanted to compare the performance of different array methods besides `slice` and `filter`, some alternatives could be:

* `map()`: Similar to `filter`, but creates a new array with transformed values.
* `reduce()`: A more complex method for reducing an array to a single value, often used in combination with other methods.
* `forEach()`: A method that executes a callback function on each element of the array without creating a new array.

Keep in mind that these alternatives may have different trade-offs and characteristics compared to `slice` and `filter`, so it's essential to consider your specific use case and requirements when choosing an alternative.

Related benchmarks:

slice vs filter 2 (version: 0)

slice vs filter

Comparing performance of: slice vs filter

Created: 4 years ago by: Guest

Jump to the latest result

slice

filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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