Benchmark: testesttestest - MeasureThat.net

Tests:

slice + concat
const buyerGalleryData = { adminVideos: null, adminImages: [{url: '1'},{url: '2'},{url: '3'}], videos: [{url: '1'},{url: '2'},{url: '3'}], images: null } ; const numOfMediaToShow =4; let count = 0; let mediaDisplayData= []; for (const [key, mediaData] of Object.entries(buyerGalleryData)) { if (count === numOfMediaToShow) { break; } if (mediaData) { const requiredNumOfMedia = numOfMediaToShow - count; const mediaDataLength = mediaData.length; const numOfMediaToAdd = Math.min(requiredNumOfMedia, mediaDataLength); mediaDisplayData = mediaDisplayData.concat( mediaData.slice(0, numOfMediaToAdd), ); count += numOfMediaToAdd; } console.log(mediaDisplayData); } return mediaDisplayData;
loop
const buyerGalleryData = { adminVideos: null, adminImages: [{url: '1'},{url: '2'},{url: '3'}], videos: [{url: '1'},{url: '2'},{url: '3'}], images: null }; const numOfMediaToShow =4; let count = 0; let mediaDisplayData = []; for (const [key, mediaData] of Object.entries(buyerGalleryData)) { if (count === numOfMediaToShow) { break; } if (mediaData) { const isVideoMedia = key === 'adminVideos' || key === 'videos'; for (const media of mediaData) { mediaDisplayData.push({ ...media, type: isVideoMedia ? 'video' : 'image', }); count++; if (count === numOfMediaToShow) { break; } } } } return mediaDisplayData;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice + concat
loop

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, along with the pros and cons of each approach.

**Benchmark Overview**

The test cases measure the performance of two different ways to process an object containing media data (videos and images). The goal is to display a subset of media items based on a specified limit (`numOfMediaToShow`).

**Test Case 1: "slice + concat"**

This test case uses the `Array.prototype.slice()` method to extract a portion of the `mediaData` array and then concatenates it with an empty array using `Array.prototype.concat()`. The resulting array is then returned.

Pros:

* This approach is simple and efficient, as it directly manipulates the original data without creating unnecessary intermediate arrays.
* It's easy to read and understand, making it a good choice for developers familiar with JavaScript basics.

Cons:

* Creating a new array using `concat()` can lead to increased memory allocation and garbage collection overhead, potentially impacting performance.
* This approach assumes that the media data is already in an array format; if not, additional processing might be required before applying this method.

**Test Case 2: "loop"**

This test case uses a traditional loop structure to iterate through the `mediaData` object. For each iteration, it creates a new object with the same properties as the original media item and adds a `type` property indicating whether it's a video or image. The resulting array is then returned.

Pros:

* This approach provides more control over the processing pipeline, allowing for additional logic to be applied during each iteration.
* It doesn't require creating intermediate arrays, which can reduce memory allocation and garbage collection overhead.

Cons:

* This approach is more verbose and complex than the "slice + concat" method, making it less readable for developers unfamiliar with JavaScript.
* The loop structure may lead to performance issues if not optimized properly, especially for large datasets.

**Library Used: None**

There are no libraries used in these test cases. However, the `Object.entries()` method is used to iterate through the object's properties and values.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntax used in these test cases that would require additional explanation.

**Other Alternatives**

Alternative approaches to these two methods include:

1. Using `Array.prototype.reduce()` to aggregate the media data into a single array.
2. Employing a more functional programming style using arrow functions and `Map` objects to process the media data.
3. Utilizing a library like Lodash to provide additional utility functions for working with arrays and objects.

These alternatives might offer different trade-offs in terms of performance, readability, and memory usage, but they can provide an interesting perspective on solving this problem.

**Benchmark Interpretation**

The benchmark results show that the "loop" test case outperforms the "slice + concat" method in terms of executions per second. This is likely due to the reduced overhead associated with creating intermediate arrays using `concat()`. However, the actual performance difference may depend on the specific use case and the characteristics of the media data being processed.

In conclusion, both test cases have their strengths and weaknesses, and the choice between them depends on the specific requirements and constraints of the project.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36

Browser/OS: Chrome 105 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
slice + concat	109283.8 Ops/sec
loop	990533.5 Ops/sec

Related benchmarks:

testesttestest (version: 0)

Comparing performance of: slice + concat vs loop

Created: 2 years ago by: Guest

Jump to the latest result

slice + concat

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):