Benchmark: slice VS splice VS shift: who is the fastest to remove multiple items

Script Preparation code:

var list = [];
for (var i = 0; i < 1000 * 1000; i++) {
  list.push(i);
}

var list2 = [...list]
var list3 = [...list]

Tests:

slice
list = list.slice(50);
splice
list2.splice(0, 50);
shift
for (let i = 0; i < 50; ++i) list3.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):

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Let's break down the provided benchmark and explain what's being tested, compared options, pros and cons of those approaches, and other considerations.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmarking test case. The goal is to measure which method (slice, splice, or shift) is the fastest for removing multiple items from an array.

**Options Compared**

Three methods are being tested:

1. **Slice**: Using `list.slice(50)` to remove 50 elements from the beginning of the array.
2. **Splice**: Using `list.splice(0, 50)` to remove the first 50 elements from the array.
3. **Shift**: Using a `for` loop with `list.shift()` to remove and return each element until 50 elements are removed.

**Pros and Cons**

1. **Slice**:
	* Pros: Creates a new array object that references the original array's contents, which is more memory-efficient. It doesn't modify the original array.
	* Cons: Can be slower due to the overhead of creating a new array object. The created array is not bound to the garbage collector, so it remains in memory even after the original array is freed.
2. **Splice**:
	* Pros: Modifies the original array and does not create a new array object.
	* Cons: Can be slower due to the overhead of modifying an array's internal structure. The modified array's length is updated, which can lead to issues with indexing and iteration.
3. **Shift**:
	* Pros: Removes elements from the original array without creating a new one.
	* Cons: Uses a `for` loop, which can be slower than other methods due to the overhead of loop control and iteration.

**Other Considerations**

* The benchmark uses an array with 1 million elements, which is a large enough size to demonstrate performance differences between these methods.
* The use of `var` instead of `let` or `const` for variable declarations might impact performance in some browsers, as `var` can lead to hoisting and scope issues.

**JavaScript Features**

The benchmark does not explicitly test any special JavaScript features like `async/await`, ` generators`, or `Symbol`. However, it's worth noting that the use of an array with a large number of elements might expose performance differences due to how JavaScript handles arrays in memory.

**Libraries and Frameworks**

There are no external libraries or frameworks being used in this benchmark. The code relies solely on standard JavaScript features.

**Alternatives**

Other alternatives for removing multiple items from an array could include:

* `Array.prototype.forEach()`: Iterating over the array and using `array.splice()` to remove elements.
* `Array.prototype.filter()`: Creating a new array with filtered elements.
* Using a different data structure, like a linked list or a stack, which might have better performance characteristics for certain use cases.

In summary, this benchmark tests the performance of three common methods for removing multiple items from an array in JavaScript: slice, splice, and shift. The results will help users understand the trade-offs between these methods and make informed decisions about how to optimize their code for specific performance requirements.

Related benchmarks:

slice VS splice VS shift: who is the fastest to remove multiple items (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: 2 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):