Benchmark: Slice vs splice vs filter

Script Preparation code:

var arr = [];

for (var i = 0; i < 1000000; i++) {
  arr.push(Math.floor(Math.random() * 100))
}

var idx = 550000

Tests:

Slice
arr.slice(0, idx).concat(arr.slice(idx+1));
Filter
arr.filter((_,i) => i !== idx);
For Loop
var newarr = []; for (var i = 0; i < arr.length; i++) { if (i !== idx) { newarr.push(arr[i]) } }
Spread and Splice
var newarr2 = [...arr]; newarr2.splice(idx, 1);
Splice
arr.splice(idx, 1);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Slice
Filter
For Loop
Spread and Splice
Splice

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

The provided JSON represents a JavaScript microbenchmarking test case on the MeasureThat.net website. The benchmark measures the performance of different approaches to split, filter, or manipulate an array.

**Tested Approaches:**

1. **Slice**: This approach uses the `slice()` method to create a new array that includes all elements before and after the specified index.
2. **Filter**: This approach uses the `filter()` method to create a new array that excludes elements at the specified index.
3. **For Loop**: This approach uses a traditional for loop to iterate through the array, excluding the element at the specified index from being added to a new array.
4. **Spread and Splice**: This approach uses the spread operator (`...`) to create a copy of the original array, and then splices out the element at the specified index using `splice()`.
5. **Splice**: This approach directly calls `splice()` on the original array to remove the element at the specified index.

**Pros and Cons:**

1. **Slice**:
	* Pros: Simple and efficient, as it only creates a new array reference.
	* Cons: Can be slower if the slice is too large, as it needs to create a new array with all elements before and after the specified index.
2. **Filter**:
	* Pros: Only modifies the original array, making it more memory-efficient for large datasets.
	* Cons: Slower than other approaches, as it iterates through the entire array to find elements that meet the condition.
3. **For Loop**:
	* Pros: Allows for direct manipulation of the original array and can be faster if the slice is small.
	* Cons: More complex code and potentially slower than other approaches due to loop overhead.
4. **Spread and Splice**:
	* Pros: Creates a new array copy, which can be beneficial for large datasets, and avoids modifying the original array.
	* Cons: Can be slower than other approaches due to the spread operator's overhead, and requires additional memory allocation.
5. **Splice**:
	* Pros: Directly modifies the original array, making it more efficient in terms of memory usage.
	* Cons: Slower than other approaches due to the `splice()` method's overhead.

**Library Usage:**

None of the provided benchmarks use external libraries.

**Special JavaScript Features:**

The benchmark uses the spread operator (`...`) which is a feature introduced in ECMAScript 2015 (ES6). It allows for creating new arrays from existing arrays, objects, or other iterable sources.

Other Considerations:

* The test case generates a large array of random integers and then slices, filters, or manipulates it using the different approaches.
* The benchmark measures the number of executions per second, which indicates performance.
* The results show that **Slice** is generally the fastest approach, followed by **Spread and Splice**, while **Filter** and **For Loop** are slower.

Alternative Approaches:

Other possible approaches to split or filter an array could include:

* Using `Array.prototype.map()` and then concatenating or filtering the resulting arrays.
* Utilizing `lodash` library functions like `pick` (filter) or `slice` (split).
* Implementing custom iteration logic using `for...of` loops or recursive functions.

Note that these alternative approaches might not be covered in this benchmark, and their performance may vary depending on the specific use case and implementation.

Related benchmarks:

Slice vs splice vs filter (version: 0)

Comparing performance of: Slice vs Filter vs For Loop vs Spread and Splice vs Splice

Created: 3 years ago by: Guest

Jump to the latest result

Slice

Filter

For Loop

Spread and Splice

Splice

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):