Benchmark: slice VS splice VS shift: who is the fastest to keep constant size - 100

Script Preparation code:

var list = [];
for (var i = 0; i < 100; i++) {
  list.push(i);
}

Tests:

slice
list.push('slice'); list = list.slice(1);
splice
list.push('splice'); list.splice(0, 1);
shift
list.push('splice'); list.shift();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
splice
shift

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

**Overview**

The provided JSON represents a JavaScript benchmark test case on the MeasureThat.net website. The goal is to compare the performance of three different approaches: using `slice()`, `splice()`, and `shift()` methods to manipulate an array.

**Test Case Breakdown**

1. **Original Benchmark Definition**: The original script pushes 100 elements onto an empty array, then defines a benchmark that compares the execution time of three variations:
	* `list.push('slice'); list = list.slice(1);`
	* `list.push('splice'); list.splice(0, 1);`
	* `list.push('shift'); list.shift();`

These benchmarks test who is the fastest to keep the same size of the array while removing elements.

2. **Individual Test Cases**: Each individual test case represents one of the three variations:
	* `slice()`: Pushes 'slice' onto the array, then uses `slice()` to remove the first element.
	* `splice()`: Pushes 'splice' onto the array, then uses `splice()` with the first element as an argument.
	* `shift()`: Pushes 'shift' onto the array, then uses `shift()` to remove the first element.

**Comparison of Approaches**

1. **Slice()**: Creates a new copy of the array using `slice()`, which is slower than other approaches because it requires additional memory allocation and copying.
	* Pros: Easy to read and understand, creates a clean separation between the original data and the modified slice.
	* Cons: Requires more memory allocation and copying, resulting in higher overhead.
2. **Splice()**: Modifies the original array in place using `splice()`, which can be faster than other approaches because it only modifies the existing array elements.
	* Pros: Faster execution time, as it avoids creating a new copy of the data.
	* Cons: Can modify the original array, potentially affecting its integrity or stability.
3. **Shift()**: Removes the first element from the array using `shift()`, which is likely to be the fastest approach because it directly removes elements without creating a new copy.
	* Pros: Fastest execution time, as it only involves removing elements directly from the original array.
	* Cons: May not be suitable for all scenarios, as it modifies the original data.

**Library Considerations**

None of the test cases explicitly use any libraries beyond JavaScript's built-in methods.

**Special JS Feature/Syntax**

The `slice()` method uses a non-standard notation (`list = list.slice(1)`) to create a new slice of the array. In modern JavaScript, this would be written as `const slicedList = list.slice(1);`. The use of 'splice' and 'shift' methods is standard.

**Alternatives**

Other approaches could have been used in place of these three:

* Using `Array.prototype.forEach()` to iterate over the array elements and remove them.
* Using `Array.prototype.map()` to create a new array with modified elements.
* Using a loop to manually increment an index variable, effectively removing elements from the original array.

However, it's worth noting that using `slice()`, `splice()`, or `shift()` methods is often the most straightforward and efficient way to manipulate arrays in JavaScript.

Related benchmarks:

slice VS splice VS shift: who is the fastest to keep constant size - 100 (version: 0)

100k list splice and shift win, they mutate list slice loose, it creates a copy of list 7.5x slower

Comparing performance of: slice vs splice vs shift

Created: 4 years ago by: Guest

Jump to the latest result

slice

splice

shift

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):