Benchmark: slice().splice(low, howmany) vs slice(low, low + howmany) big

Script Preparation code:

var total = 1000000;
var low = 50;
var howmany = 10;
var data = new Array(total).fill(undefined).map((_, i) => i);

Tests:

slice().splice(low, howmany)
var page = data.slice().splice(low, howmany);
slice(low, low + howmany)
var page = data.slice(low, low + howmany)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice().splice(low, howmany)
slice(low, low + howmany)

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its test cases to understand what's being measured.

**Benchmark Overview**

The benchmark is comparing two approaches for slicing an array: `slice().splice(low, howmany)` and `slice(low, low + howmany)`. The goal is to determine which approach performs better in terms of execution speed.

**What are we testing?**

We're testing the performance difference between these two methods when used on a large array (`data`) with a specific range (`low` to `low + howmany`). The test case uses a JavaScript function, `slice()`, which returns a shallow copy of a portion of an array.

**Options being compared**

The two options being compared are:

1. **`slice().splice(low, howmany)`**: This method modifies the original array by removing `howmany` elements starting from index `low`. It returns the removed elements as an array.
2. **`slice(low, low + howmany)`**: This method creates a shallow copy of a portion of the array, starting at index `low` and ending at index `low + howmany`.

**Pros and Cons**

1. **`slice().splice(low, howmany)`**:
	* Pros: Can be more efficient when dealing with large arrays, as it modifies the original array in place.
	* Cons: Returns the removed elements as an array, which can lead to additional memory allocation and garbage collection overhead.
2. **`slice(low, low + howmany)`**:
	* Pros: Creates a shallow copy of the array portion, avoiding potential modification of the original array and reducing memory allocation.
	* Cons: Requires more memory allocation and copying, especially for large arrays.

**Library usage**

There is no library used in this benchmark. The test case only uses built-in JavaScript functions (`slice()`).

**Special JS feature or syntax**

The benchmark does not use any special JavaScript features or syntax beyond the standard `slice()` function.

**Other alternatives**

Some alternative approaches to consider:

1. **Using `Array.prototype.slice.call()`**: This method creates a shallow copy of an array, similar to `slice()`, but can be more efficient for large arrays.
2. **Using `Array.prototype.substring()`**: This method creates a shallow copy of a portion of an array, similar to `slice()`, but can be slower due to the overhead of substring creation.
3. **Using a library like Lodash's `cloneDeep()`**: This function creates a deep copy of an object or array, which can be useful when dealing with complex data structures.

Keep in mind that the benchmark is focused on comparing the performance of these two specific methods, so exploring alternative approaches may not yield significant improvements for this particular use case.

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:68.0) Gecko/20100101 Firefox/68.0

Browser/OS: Firefox 68 on Windows

View result in a separate tab

Test name	Executions per second
slice().splice(low, howmany)	52.0 Ops/sec
slice(low, low + howmany)	4612143.0 Ops/sec

Related benchmarks:

slice().splice(low, howmany) vs slice(low, low + howmany) big (version: 0)

Checking performance between slice().splice(low, howmany) and slice(low, low + howmany)

Comparing performance of: slice().splice(low, howmany) vs slice(low, low + howmany)

Created: 5 years ago by: Guest

Jump to the latest result

slice().splice(low, howmany)

slice(low, low + howmany)

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):