Benchmark: SpreadVSPush - MeasureThat.net

HTML Preparation code:


<div id=''></div>

Tests:

1
const arr = [1, 2,3] acc.push(4)
2
const arr = [1, 2,3] const arr1 = [...arr, 4]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and its various aspects.

**Benchmark Overview**

The SpreadVSPush benchmark measures the performance difference between two approaches to push elements onto an array in JavaScript: using the `push()` method and using the spread operator (`...`). The benchmark is designed to test the speed of these operations on a small dataset.

**Script Preparation Code**

The script preparation code is empty, which means that no custom code is executed before running each test case. This allows the benchmark to focus solely on measuring the performance of the JavaScript engine's array operations.

**Html Preparation Code**

The HTML preparation code creates a simple container element (`<div>`) with an ID, which is likely used for rendering or displaying the results in some way. However, this code does not affect the performance being measured and can be ignored.

**Test Cases**

There are two test cases:

1. **Test Case 1**: This test case measures the time it takes to push a single element onto an array using `push()`. The benchmark definition is:
```javascript
const arr = [1, 2,3]
acc.push(4)
```
This code creates an array `arr` with three elements and then pushes a fourth element onto it using the `push()` method.

2. **Test Case 2**: This test case measures the time it takes to create a new array by spreading the original array and pushing a single element onto it. The benchmark definition is:
```javascript
const arr = [1, 2,3]
const arr1 = [...arr, 4]
```
This code creates an array `arr` with three elements and then uses the spread operator (`...`) to create a new array `arr1`, which includes the original elements followed by a single additional element.

**Pros and Cons of Each Approach**

* **push() method**: This approach is generally faster because it modifies the existing array in-place, avoiding the overhead of creating a new array. However, it may not be suitable for large datasets or when the original order of elements needs to be preserved.
* **Spread operator (`...`)**: This approach creates a new array with a copy of the original elements and then pushes the additional element onto it. While this approach can be useful in certain situations (e.g., when preserving the original order), it may be slower due to the overhead of creating a new array.

**Other Considerations**

* **Array creation**: Both approaches require creating an array, which can be expensive in terms of memory allocation and garbage collection.
* **Element insertion**: The benchmark measures the time taken to insert an element into the existing array. This is a common operation in many applications, so understanding its performance characteristics is important.

**Library Usage**

There are no libraries used in this benchmark definition. However, if any libraries were used, they would likely be built-in JavaScript functionality or third-party libraries like `lodash` or `ramda`.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax mentioned in the benchmark definitions.

**Alternatives**

If you need to benchmark other array operations or techniques, you may consider exploring the following alternatives:

* **Array methods**: Other array methods like `unshift()`, `concat()`, and `slice()` can be used instead of `push()`.
* **Native methods**: Some browsers provide native methods for array operations, such as WebAssembly's `Vec` type or some proprietary extensions.
* **Third-party libraries**: Libraries like `lodash` or `ramda` offer optimized implementations for various array operations.

Keep in mind that the best approach will depend on the specific requirements and constraints of your project.

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.70 Safari/537.36 Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.121 Safari/537.36

Browser/OS: Chrome 78 on Windows

View result in a separate tab

Test name	Executions per second
1	0.0 Ops/sec
2	11002040.0 Ops/sec

Related benchmarks:

SpreadVSPush (version: 0)

Comparing performance of: 1 vs 2

Created: 5 years ago by: Guest

Jump to the latest result

1

2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):