Benchmark: asdasdasfasd - MeasureThat.net

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

function tt(i) {
	console.log(i);
}

function times(t, fn) {
  for (let i = 0; i < t; i++) {
    fn(i);
  }
}

Tests:

lodash
_.times(10, tt);
vanilla
times(10, tt);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
vanilla

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.

Let's break down what's being tested in this JavaScript microbenchmark, MeasureThat.net.

**Benchmark Definition:**
The benchmark definition is an object that describes the test case. In this example, there are two test cases:

1. "_.times(10, tt);" - This is a benchmarking a specific function call using the Lodash library's `times` function, which repeats a given function (`tt`) for a specified number of times (in this case, 10).
2. "times(10, tt);" - This is a benchmarking a custom implementation of the same logic as above, without using any external libraries.

**Options Compared:**
The two options being compared are:

* Using an external library (Lodash) to implement a repetitive function call
* Implementing the same logic from scratch, without relying on any external libraries

**Pros and Cons:**

Using an external library (Lodash):

Pros:

* Faster development time, as you don't need to write and test your own implementation
* Potential for better performance, since the library is optimized and tested for performance
* Simplified code, as you can use existing functionality without worrying about implementing it yourself

Cons:

* Additional dependency to manage (Lodash needs to be included in the project)
* Potential security risks if using an untrusted or outdated version of the library
* May not be suitable for all projects, especially those with strict licensing requirements

Implementing from scratch:

Pros:

* Complete control over the implementation and its dependencies
* No risk of security vulnerabilities or licensing issues
* Potential for improved performance, since you can optimize your own code specifically for the task

Cons:

* More time-consuming to develop and test your own implementation
* May require more expertise in optimization and testing techniques

**Library:**
The Lodash library is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, string processing, and function creation.

In this benchmark, the `times` function from Lodash is used to repeat the `tt` function 10 times. This allows for a controlled and consistent test case, which can help identify performance differences between using an external library versus implementing from scratch.

**Special JS Feature/Syntax:**
There are no special JavaScript features or syntaxes being tested in this benchmark. The code is straightforward and does not use any advanced language features such as async/await, destructuring, or object-oriented programming.

**Alternatives:**
If you were to implement a similar benchmark without using MeasureThat.net, you could consider the following alternatives:

1. Benchmarking frameworks like `benchmark.js`, `js-benchmark`, or `micro-benchmark`
2. Online platforms for benchmarking and testing, such as `jsperf` or `jsbench`
3. In-house tools and scripts for automating benchmarking and performance testing

Keep in mind that these alternatives might have different features, flexibility, and ease of use compared to MeasureThat.net.

Related benchmarks:

asdasdasfasd (version: 0)

asfasdasfasdasf

Comparing performance of: lodash vs vanilla

Created: 3 years ago by: Guest

Jump to the latest result

lodash

vanilla

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):