Benchmark: childNodes - Two calls

HTML Preparation code:

<ul id="list">
  <li>01</li>
  <li>02</li>
  <li>03</li>
  <li>04</li>
  <li>05</li>
  <li>06</li>
  <li>07</li>
  <li>08</li>
  <li>09</li>
  <li>10</li>
</ul>

Script Preparation code:

var list=document.querySelector('#list');

function childAt(el, index) {
  let child = el.firstChild
  if (index) {
    for (let j = 0; j < index; ++j) {
      if (!child) break;
      child = child.nextSibling;
    }
  }
  return child;
}

Tests:

childNodes
list.childNodes[3]; list.childNodes[4]
loop
childAt(list, 3); childAt(list, 4)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
childNodes
loop

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The benchmark measures the performance of accessing child nodes in a DOM element using two different approaches:

1. Direct access: `list.childNodes[3]; list.childNodes[4]`
2. Loop-based approach: `childAt(list, 3); childAt(list, 4)`

**Options Compared**

There are two options being compared:

1. **Direct Access**: Using the `childNodes` property to directly access specific child nodes by their index.
2. **Loop-based Approach**: Implementing a custom function `childAt` that loops through the child nodes to find the desired node.

**Pros and Cons of Each Option**

1. **Direct Access**:
	* Pros: Simple, straightforward, and efficient for accessing specific child nodes.
	* Cons: May not work well for large datasets or when dealing with complex DOM structures, as it relies on direct indexing which can be slow.
2. **Loop-based Approach**:
	* Pros: Flexible, scalable, and can handle large datasets, but may introduce overhead due to the loop.
	* Cons: More complex, may have performance implications due to the loop, and requires additional code.

**Library Used**

The `childAt` function uses a library called `node.js` (not explicitly mentioned in the JSON), which provides the necessary DOM manipulation APIs. In this case, it's used for accessing child nodes.

**Special JS Features/Syntax**

There is no special JavaScript feature or syntax being tested or used in this benchmark. The code relies on standard DOM APIs and JavaScript functions.

**Other Considerations**

* The benchmark uses a fictional `list` element with 10 child nodes, which may not represent real-world scenarios.
* The test cases assume that the `childAt` function is implemented correctly and can find the desired node in O(1) time complexity.
* The benchmark results are provided for Chrome 115 on Linux Desktop platforms.

**Alternatives**

Some alternative approaches to accessing child nodes could include:

1. Using a more advanced data structure, such as a balanced tree or a hash table, to store child nodes and improve lookup efficiency.
2. Utilizing JavaScript libraries like React or Angular, which provide optimized DOM manipulation APIs for large-scale applications.
3. Employing native WebAssembly (WASM) or WebGPU for better performance in browser-based applications.

Keep in mind that these alternatives might not be relevant to this specific benchmark, but they could be explored in other scenarios where accessing child nodes is a critical performance bottleneck.

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36

Browser/OS: Chrome 115 on Linux

View result in a separate tab

Test name	Executions per second
childNodes	4808203.0 Ops/sec
loop	3476634.5 Ops/sec

Related benchmarks:

childNodes - Two calls (version: 2)

Comparing performance of: childNodes vs loop

Created: one year ago by: Registered User

Jump to the latest result

childNodes

loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):