Benchmark: Splice vs Filter

Script Preparation code:


var arr = [{id: 3, name: 'foo'}, {id: 9, name: 'foo'}, {id: 14, name: 'foo'}, {id: 83, name: 'foo'}, {id: 72, name: 'foo'}, {id: 16, name: 'foo'}, {id: 12, name: 'foo'}, {id: 4, name: 'foo'}, {id: 234, name: 'foo'}];

Tests:

Filter
return arr = arr.filter(a => a.id !== 12)
Splice
var index = arr.indexOf(a => a.id === 12) arr.splice(index, 1) return arr

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Filter
Splice

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36

Browser/OS: Chrome 124 on Windows

View result in a separate tab

Test name	Executions per second
Filter	5918674.5 Ops/sec
Splice	5437998.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and analyze the provided benchmark.

**What is being tested?**

The benchmark is comparing two approaches to remove an element from an array: `filter` and `splice`.

**Options compared:**

* `filter`: uses a callback function to create a new array with elements that pass a certain test (in this case, `a.id !== 12`)
* `splice`: uses the `indexOf` method to find the index of the element to be removed and then removes it using the `splice` method

**Pros and Cons:**

* **Filter**:
	+ Pros: efficient, simple, and expressive way to create a new array with filtered elements
	+ Cons: creates a new array, which can be memory-intensive for large datasets
* **Splice**:
	+ Pros: modifies the original array, potentially faster for small datasets since it avoids creating a new array
	+ Cons: modifies the original array, which may not be desirable in some cases. Also, `splice` has to search for the element to remove, which can be slower than `filter`

Other considerations:

* **Performance**: Both approaches have their trade-offs in terms of performance. For large datasets, `filter` might be faster since it avoids modifying the original array and doesn't require searching for the element to remove.
* **Memory usage**: As mentioned earlier, `filter` creates a new array, which can be memory-intensive. On the other hand, `splice` modifies the original array, which may lead to memory leaks if not handled properly.

**Library/Functions used:**

None are explicitly mentioned in the provided code snippets.

**Special JS feature/syntax:**

* **Arrow functions**: Both benchmark definitions use arrow functions (`a => a.id !== 12`) as the callback function for `filter`. Arrow functions are a concise way to define small, one-time-use functions.
* **Template literals**: The `Script Preparation Code` uses template literals (`\r\nvar arr = [...];`) to create a string with multiple lines.

**Other alternatives:**

If you want to explore other approaches, here are a few options:

* **forEach**: Instead of using `filter` or `splice`, you could use the `forEach` method to iterate over the array and remove elements manually. This would involve creating an iterator object and iterating over it.
* **map`: You could use `map` to create a new array with filtered elements, which might be more efficient than `filter` for very large datasets.

For example:
```javascript
arr.forEach((a, index) => {
  if (index === 3) { // Remove the element at index 3
    arr.splice(index, 1);
  }
});
```
Keep in mind that this approach would have its own trade-offs in terms of performance and memory usage.

Related benchmarks:

Splice vs Filter (version: 0)

Comparing performance of: Filter vs Splice

Created: 7 years ago by: Guest

Jump to the latest result

Filter

Splice

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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