Benchmark: matches vs. dataset

HTML Preparation code:

<div data-message-author-role="user" data-message-id="aaa2f94a-7680-4be5-b642-58b1cfb98519" class="min-h-[20px] text-message flex flex-col items-start gap-3 whitespace-pre-wrap break-words [.text-message+&amp;]:mt-5 overflow-x-auto">
</div>

Tests:

matches
var element = document.querySelector(".text-message"); var i = 1000; while (i--) { element.matches("div[data-message-author-role='user']"); }
data
var element = document.querySelector(".text-message"); var i = 1000; while (i--) { element.dataset.messageAuthorRole === "user" }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
matches
data

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 10 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
matches	26548.9 Ops/sec
data	16008.9 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases to explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark is defined by a JSON object that contains information about the benchmark itself:

* `Name`: The name of the benchmark, which is "matches vs. dataset".
* `Description`: An empty string indicating no description.
* `Script Preparation Code` and `Html Preparation Code`: These are used to set up the test environment.

**Individual Test Cases**

There are two test cases defined within the benchmark:

1. **"matches"`**
```javascript
var element = document.querySelector(".text-message");
var i = 1000;
while (i--) {
    element.matches("div[data-message-author-role='user']");
}
```
This test case uses the `matches()` method to check if the `element` matches a CSS selector. The selector is a div with an attribute `data-message-author-role` set to `'user'`. The test repeats this check 1000 times.

Pros:

* Simple and concise code.
* Easy to understand.

Cons:

* May be slow due to repeated DOM queries.

2. **"data"`**
```javascript
var element = document.querySelector(".text-message");
var i = 1000;
while (i--) {
    element.dataset.messageAuthorRole === "user";
}
```
This test case uses the `dataset` property to access and compare a value with a string literal. The test repeats this comparison 1000 times.

Pros:

* Fast due to direct access to `dataset`.
* Avoids repeated DOM queries.

Cons:

* May be slower for large datasets or complex conditions.
* Requires knowledge of how `dataset` works in modern browsers.

**Library and Special JS Features**

In both test cases, the `document.querySelector()` function is used. This is a built-in JavaScript method that selects an element from the DOM based on a CSS selector.

The `dataset` property is also used in the "data" test case, which is a part of the HTML5 specification. It allows elements to store and retrieve key-value pairs as attributes, which can be accessed using dot notation (e.g., `element.dataset.messageAuthorRole`).

No special JavaScript features or syntax are required for these tests.

**Other Alternatives**

For this benchmark, other alternatives could include:

1. Using a different CSS selector engine, such as Sizzle or CSSOM.
2. Implementing a custom matching algorithm using regex or string manipulation.
3. Measuring the performance of alternative DOM traversal methods, such as `getElementById()` or `getElementsByClassName()`.
4. Creating a test case that exercises other browser-specific features, such as WebAssembly or Web Workers.

However, these alternatives might not be directly relevant to this specific benchmark, which focuses on comparing two simple test cases involving `matches()` and `dataset`.

Related benchmarks:

matches vs. dataset (version: 0)

Comparing performance of: matches vs data

Created: 10 months ago by: Registered User

Jump to the latest result

matches

data

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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