Benchmark: wersdfsdfsd - MeasureThat.net

Tests:

test 1
let colores = ["A", "B", "C", "D", "F", "G", "##"]; function removerElementos(elemento) { return elemento !== "##"; } let resultado1 = colores.filter(removerElementos);
test 2
let colores = ["A", "B", "C", "D", "F", "G", "##"]; let resultado2 = colores.filter(function (elemento) { return elemento !== "##"; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
test 1
test 2

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

I'd be happy to help you understand what's being tested in this JavaScript microbenchmark.

**Overview**

The benchmark consists of two test cases that measure the performance of filtering an array of colors using different approaches.

**What is being tested?**

* The first test case uses a simple arrow function (`() => { ... }`) as the filter callback, while the second test case uses a traditional function declaration (`function (elemento) { ... }`).
* Both tests create an array `colores` containing color codes and define a function `removerElementos` that returns `true` if the element is not equal to `"##"`. The filter method is then applied to the `colores` array, removing elements based on this condition.

**Options compared**

The two options being compared are:

1. **Arrow function (`() => { ... }`)**
	* Pros:
		+ Concise and expressive syntax.
		+ Faster execution due to compile-time optimizations by modern JavaScript engines (e.g., V8).
	* Cons:
		+ May not be supported in older browsers or Node.js versions.
2. **Traditional function declaration (`function (elemento) { ... }`)**

**Other considerations**

The benchmark also considers the following factors:

* Array length: Although not explicitly mentioned, it's likely that the array size is small and uniform across both tests.
* JavaScript engine: The tests are run on Chrome 84, which may have optimized functions for arrow functions.
* Platform and device: The test runs on a Windows desktop, which might affect performance.

**Library usage**

There is no library being used in these test cases.

**Special JS features or syntax**

Neither test case uses any special JavaScript features or syntax beyond the two options mentioned above (arrow function vs. traditional function declaration).

**Alternative approaches**

Other ways to implement this filter could include:

* Using a `for...of` loop instead of `filter()`
* Utilizing `map()` with a callback function
* Leveraging `Array.prototype.every()` or `Array.prototype.some()`

Keep in mind that these alternatives might not be as concise or readable as the arrow function and traditional function declaration approaches used in the benchmark.

Now, if you'd like me to elaborate on any of these points or discuss potential optimizations for this particular filter algorithm, feel free to ask!

Related benchmarks:

wersdfsdfsd (version: 0)

werwerw

Comparing performance of: test 1 vs test 2

Created: 5 years ago by: Guest

Jump to the latest result

test 1

test 2

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):