Benchmark: max vs arrat - MeasureThat.net

HTML Preparation code:

<div style="width: 10px;"></div>
<div style="width: 20px;"></div>
<div style="width: 30px;"></div>
<div style="width: 40px;"></div>
<div style="width: 50px;"></div>
<script src="//ajax.googleapis.com/ajax/libs/jquery/1/jquery.min.js"></script>

Tests:

array
var existingWidth = new Array(); $('div').each(function(){ existingWidth.push($(this).outerWidth()); }); existingWidth.sort(function(a, b){return b-a}); console.log(existingWidth[0]);
max
var existingWidth = 0; $('div').each(function(){ if ($(this).outerWidth() > existingWidth) { existingWidth = $(this).outerWidth(); } }); console.log(existingWidth);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array
max

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

**What is being tested?**

MeasureThat.net is testing two different approaches to finding the maximum width of HTML elements on a webpage: using an array and using a single variable.

The first test case, "array", uses an array to store the widths of all the HTML elements found on the page. The script then sorts the array in descending order and logs the widest element's width to the console. This approach requires iterating over each element, pushing its width into the array, sorting the array, and finally accessing the first element (which is the widest) using `existingWidth[0]`.

The second test case, "max", uses a single variable, `existingWidth`, to store the maximum width found so far. The script iterates over each element, checks if its width is greater than the current maximum, and updates the maximum width if necessary. This approach requires fewer iterations compared to the array-based method.

**Options comparison**

There are two primary options being compared:

1. **Array-based approach**: This approach uses an array to store all the widths and sorts it in descending order to find the widest element.
	* Pros:
		+ Can handle a large number of elements, as it stores them in memory.
		+ Allows for easy iteration over each element's width.
	* Cons:
		+ Requires more memory to store the array.
		+ Sorting the array can be computationally expensive for large datasets.
2. **Single variable approach**: This approach uses a single variable to keep track of the maximum width found so far.
	* Pros:
		+ Uses less memory compared to the array-based approach.
		+ Iterations are faster, as it only checks if the current element's width is greater than the existing maximum.

**Other considerations**

Both approaches have trade-offs:

* **Memory usage**: The array-based approach requires more memory, especially for large datasets. The single variable approach uses less memory but might not be suitable for very large datasets.
* **Computational complexity**: Sorting the array can be computationally expensive, whereas checking if a value is greater than another value using a single assignment operation is relatively fast.

**Library usage**

MeasureThat.net uses jQuery in its scripts. jQuery is a popular JavaScript library that provides a set of functions to simplify HTML and DOM interactions. In this case, it's used for:

* `$('div')`: selects all HTML elements with the tag name "div".
* `.each()`: iterates over each element in the selected collection.
* `$(this).outerWidth()`: gets the width of an individual element.

**Special JS features or syntax**

There are no special JavaScript features or syntax used in these benchmark scripts. They use standard JavaScript constructs and libraries like jQuery.

**Alternatives**

If you wanted to implement a different approach for finding the maximum width, some alternatives could be:

* **Using `Math.max()` function**: Instead of sorting an array or updating a single variable, you can use the `Math.max()` function to find the maximum value directly.
* **Using a data structure like a heap**: If you need to handle very large datasets and want to optimize for performance, you could consider using a data structure like a heap, which is designed for efficient insertion and retrieval of maximum values.

Keep in mind that these alternatives might have different trade-offs compared to the array-based and single variable approaches used in the benchmark script.

Related benchmarks:

max vs arrat (version: 0)

Comparing performance of: array vs max

Created: 5 years ago by: Guest

Jump to the latest result

array

max

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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