Benchmark: slice vs fast slice vs filter

Script Preparation code:

var test=Array.from({length: 1000},()=>Math.random())

Tests:

slice
[...test.slice(0,50),...test.slice(51)]
filter
test.filter((e,i)=>i!=50)
fast slice
[].concat(test.slice(0,50), test.slice(51))
splice
test.splice(50, 1)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
filter
fast slice
splice

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the JavaScript microbenchmark on MeasureThat.net.

**Benchmark Definition**

The benchmark is defined in JSON format, which represents four test cases:

1. `slice`: Tests the performance of the built-in `Array.prototype.slice()` method.
2. `filter`: Tests the performance of the built-in `Array.prototype.filter()` method.
3. `fast slice`: Tests the performance of a custom implementation using `Array.prototype.concat()` to achieve similar results as `Array.prototype.slice()`.
4. `splice`: Tests the performance of the `Array.prototype.splice()` method.

**Options Compared**

The benchmark compares the performance of three different approaches:

1. **Built-in methods**: `slice` and `filter`, which are implemented in V8, the JavaScript engine used by Chrome.
2. **Custom implementation**: `fast slice`, which uses `concat()` to achieve similar results as `slice()`.
3. **Modifier method**: `splice`, which modifies the original array instead of creating a new one.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **Built-in methods` (`slice` and `filter`):
	* Pros:
		+ Optimized by V8 for performance.
		+ Typically faster than custom implementations.
	* Cons:
		+ May not be suitable for all use cases (e.g., large arrays).
2. **Custom implementation** (`fast slice`):
	* Pros:
		+ Flexible and can handle specific edge cases.
		+ Can be optimized further for performance.
	* Cons:
		+ Requires manual memory management, which can lead to bugs.
		+ May not be as performant as built-in methods.
3. **Modifier method** (`splice`):
	* Pros:
		+ Can handle large arrays efficiently by modifying the original array.
		+ Typically faster than creating a new array.
	* Cons:
		+ May leave gaps in the array if the slice size is not equal to the removed elements.
		+ Can be slower for small arrays.

**Libraries and Special Features**

None of the test cases use any external libraries. However, it's worth noting that `splice` modifies the original array, which can lead to unexpected behavior if the caller expects a new array.

**Other Alternatives**

If you're looking for alternative approaches, here are some additional methods:

1. **Array.prototype.slice()`: This is the same method tested in the benchmark.
2. **Array.prototype.subarray()`: Similar to `slice()`, but it allows specifying start and end indices as well as step values.
3. **Array.prototype.reduce()`: Can be used to achieve similar results as `slice()` or `filter()`, but it may not be as performant due to the overhead of reduction.

In summary, the benchmark provides a good comparison of different approaches for slicing an array in JavaScript. The built-in methods (`slice` and `filter`) are typically the fastest, while custom implementations like `fast slice` can offer more flexibility but may require manual optimization. The modifier method (`splice`) can handle large arrays efficiently but may leave gaps or require additional logic to fix.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.77 Safari/537.36

Browser/OS: Chrome 91 on Windows

View result in a separate tab

Test name	Executions per second
slice	86306.2 Ops/sec
filter	133420.4 Ops/sec
fast slice	541256.8 Ops/sec
splice	8463712.0 Ops/sec

Related benchmarks:

slice vs fast slice vs filter (version: 0)

Comparing performance of: slice vs filter vs fast slice vs splice

Created: 3 years ago by: Guest

Jump to the latest result

slice

filter

fast slice

splice

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):