Benchmark: buffer operations

Script Preparation code:

var buffer_to_fill = new Array(0);
var buffer_to_empty = new Array(1000);
buffer_to_empty.forEach(item => item=Math.floor(Math.random()*1000));

Tests:

push_foreach
buffer_to_empty.forEach(item => buffer_to_fill.push(item));
concat
buffer_to_fill = buffer_to_fill.concat(buffer_to_empty);
splice
buffer_to_empty = buffer_to_empty.splice(0,50);
shift
while (buffer_to_empty.length>50) { buffer_to_empty.shift(); }
push_for_loop
for (var i=0; i<buffer_to_empty.length; i++){ buffer_to_fill.push(buffer_to_empty[i]); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
push_foreach
concat
splice
shift
push_for_loop

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Android 13; Mobile; rv:109.0) Gecko/113.0 Firefox/113.0

Browser/OS: Firefox Mobile 113 on Android

View result in a separate tab

Test name	Executions per second
push_foreach	754207.2 Ops/sec
concat	282.4 Ops/sec
splice	10598691.0 Ops/sec
shift	432877760.0 Ops/sec
push_for_loop	44498.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its test cases.

**What is being tested?**

MeasureThat.net is testing the performance of different approaches for buffer operations in JavaScript. The buffers are created using the `Array` constructor, and various methods are used to manipulate them, such as `push`, `concat`, `splice`, and `shift`.

**Options compared**

The benchmark compares four different approaches:

1. **Push**: Using the `push` method to add elements to the end of the buffer.
2. **Foreach push**: Using a `for...of` loop with the `push` method to iterate over the elements of another array and add them to the end of the current buffer.
3. **Concat**: Using the `concat` method to merge two arrays into one.
4. **Splice**: Using the `splice` method to remove a specified number of elements from the beginning of the buffer.

**Pros and cons of each approach**

Here's a brief summary:

* **Push**: Pros: simple, efficient, and widely supported. Cons: can be slow for large buffers due to the overhead of creating new elements.
* **Foreach push**: Pros: can be more efficient than `push` for large buffers, as it avoids the overhead of creating new elements. Cons: requires an extra loop iteration and can be slower for small buffers.
* **Concat**: Pros: can be faster than `push` for large buffers, as it uses a more efficient algorithm to merge arrays. Cons: creates a new array and can be slower for very large inputs.
* **Splice**: Pros: can be more efficient than `push` or `concat`, especially when removing elements from the beginning of the buffer. Cons: modifies the original array and can be slower for small buffers.

**Libraries used**

None, as all operations are performed using built-in JavaScript methods.

**Special JS features or syntax**

No special features or syntax are being tested in this benchmark. However, some test cases use a `for...of` loop with the `push` method (`foreach push`), which is a relatively modern feature introduced in ECMAScript 2017 (ES6). This feature can be supported by older browsers but may not work in all environments.

**Other alternatives**

If you want to optimize buffer operations, you could also consider:

* Using typed arrays or buffers with more efficient algorithms for manipulating elements.
* Using WebAssembly for improved performance and efficiency.
* Optimizing the buffer size and allocation strategy to reduce memory fragmentation and improve performance.

Keep in mind that these optimizations might require changes to your codebase and may not be compatible with all browsers or environments.

Related benchmarks:

buffer operations (version: 0)

Comparing performance of: push_foreach vs concat vs splice vs shift vs push_for_loop

Created: one year ago by: Guest

Jump to the latest result

push_foreach

concat

splice

shift

push_for_loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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