Benchmark: Last item in array slice/0 vs length - 1 vs slice/pop vs slice/shift

Script Preparation code:

var arr = [];
for (let i = 0; i < 1000000; i++) {
  arr.push(i);
}

Tests:

slice/0
for (let i = 0; i < 1000; i++) { const v = arr.slice(-1)[0]; }
length - 1
for (let i = 0; i < 1000; i++) { const v = arr[arr.length - 1]; }
slice/pop
for (let i = 0; i < 1000; i++) { const v = arr.slice(-1).pop(); }
slice/shift
for (let i = 0; i < 1000; i++) { const v = arr.slice(-1).shift(); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice/0
length - 1
slice/pop
slice/shift

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**Benchmark Overview**

The benchmark is designed to test the performance of three different approaches for accessing the last element in an array:

1. `arr.slice(-1)[0]`
2. `arr[arr.length - 1]`
3. `arr.slice(-1).pop()`
4. `arr.slice(-1).shift()`

These approaches are commonly used, but their performance can vary depending on the JavaScript engine and browser.

**Approach Comparison**

Here's a brief summary of each approach:

### 1. `arr.slice(-1)[0]`

This approach creates a new array containing only the last element of the original array. It then accesses the first element of this new array using square brackets (`[]`). This approach has a time complexity of O(n), where n is the length of the array, because it involves creating a new array and iterating over its elements.

Pros: Simple to understand and implement.
Cons: Creates a new array, which can be memory-intensive for large arrays.

### 2. `arr[arr.length - 1]`

This approach directly accesses the last element of the original array using the index notation `arr[length - 1]`. This approach has a time complexity of O(1), making it potentially faster than the other approaches.

Pros: Directly accesses the element without creating a new array.
Cons: May not work as expected if the array is modified after access, and some browsers may optimize this operation to be slower due to bounds checking.

### 3. `arr.slice(-1).pop()`

This approach creates a new array containing only the last element of the original array (just like in Approach 1), but then immediately pops this element from the array using the `pop()` method. This approach also has a time complexity of O(n).

Pros: Creates a new array, which can be memory-efficient for large arrays.
Cons: Immediately loses access to the element after popping it.

### 4. `arr.slice(-1).shift()`

This approach creates a new array containing only the last element of the original array (just like in Approach 3), but then immediately shifts this element from the array using the `shift()` method. This approach also has a time complexity of O(n).

Pros: Creates a new array, which can be memory-efficient for large arrays.
Cons: Immediately loses access to the element after shifting it.

**Library Usage**

None of the approaches use any libraries or external dependencies.

**Special JS Features/Syntax**

There are no special JavaScript features or syntax used in these benchmarks. They focus on demonstrating basic optimization techniques and comparison of array access methods.

**Other Alternatives**

If you're looking for alternative ways to optimize array access, consider the following:

* Using `Array.prototype.at()` (introduced in ECMAScript 2020): This method provides a more efficient way to access elements at specific indices. It's supported by modern browsers and Node.js.
* Utilizing `for...of` loops: Instead of using traditional `for` loops, you can use `for...of` loops to iterate over arrays, which can be more efficient for large datasets.

Keep in mind that the performance differences between these approaches may vary depending on the specific JavaScript engine, browser, and hardware being used.

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 YaBrowser/24.7.0.0 Safari/537.36

Browser/OS: Yandex Browser 24 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
slice/0	17669.3 Ops/sec
length - 1	12801.0 Ops/sec
slice/pop	18360.7 Ops/sec
slice/shift	16331.1 Ops/sec

Related benchmarks:

Last item in array slice/0 vs length - 1 vs slice/pop vs slice/shift (version: 0)

Comparing performance of: slice/0 vs length - 1 vs slice/pop vs slice/shift

Created: 2 years ago by: Guest

Jump to the latest result

slice/0

length - 1

slice/pop

slice/shift

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):