Benchmark: eestset - MeasureThat.net

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.1/lodash.js"></script>

Script Preparation code:

function select(array, indices) {
	var arr = [];
	for (var i = 0; i < indices.length; i++) {
		var index = indices[i];
		arr.push(array[index]);
	}
	return arr;
}

var n = 1000;
var data = [];
var indices = [];

for (var i = 0; i < n; i++) {
  indices.push(i);
  data.push([ Math.random(), Math.random(), Math.random(), 1, Math.random(), Math.random(), Math.random(), 1 ]);
}

Tests:

select
var b = _.shuffle(indices); var a = b.splice(0, 5); var A = select(data, a); var B = select(data, b);
slice
var B = _.shuffle(data); var A = B.splice(0, 5);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
select
slice

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided JSON and explain what's being tested.

**Benchmark Definition**

The `Script Preparation Code` section defines a JavaScript function called `select`, which takes an array and an array of indices as input, and returns a new array with the elements at the specified indices. The `Html Preparation Code` section includes a reference to the Lodash library, specifically version 4.17.1.

**Individual Test Cases**

There are two test cases:

1. **select**: This test case uses the `select` function defined in the benchmark definition, along with the `_` (Lodash) utility function for shuffling and slicing arrays.
	* The test creates an array of indices (`indices`) and a corresponding array of data (`data`). It then shuffles the indices using Lodash's `_shuffle` function, creates two new arrays by taking the first 5 elements of the shuffled indices (`a` and `b`) using `_splice`, and finally calls the `select` function to extract subsets of data from both arrays.
2. **slice**: This test case uses a similar approach, but with the `_splice` function instead of shuffling the indices. It creates an array of data, shuffles it using Lodash's `_shuffle` function, takes the first 5 elements of the shuffled array (`B`), and then takes the first 5 elements from the beginning of the original shuffled array (`A`) using `_slice`.

**Options Compared**

The two test cases compare two different approaches:

* **Shuffling indices**: The `select` test case shuffles the indices using Lodash's `_shuffle` function, while the `slice` test case simply takes the first 5 elements of the data array.
* **Splicing vs. Shuffling**: Both tests use either `_splice` or `_shuffle` to manipulate the arrays.

**Pros and Cons**

1. **Shuffling indices**:
	* Pros: Can potentially lead to more random and varied execution orders, which can be beneficial for measuring performance under different scenarios.
	* Cons: May introduce additional overhead due to shuffling the indices.
2. **Splicing vs. Shuffling**:
	* Splicing (e.g., `_splice`) is generally faster than shuffling because it only rearranges elements in place, whereas shuffling creates a new array and copies elements.
	* However, splicing may lead to more predictable execution orders, which might not be representative of real-world use cases.

**Other Considerations**

* The use of Lodash's `_shuffle` function may introduce some bias or variability in the benchmark results due to its implementation details.
* The `select` test case uses a custom function (`_`) from Lodash, while the `slice` test case relies on built-in array methods. This could lead to differences in performance depending on how JavaScript engines optimize these operations.

**Alternatives**

If you wanted to modify or replace these test cases, here are some alternative approaches:

* Instead of shuffling indices, use a fixed sequence of numbers to create a predictable execution order.
* Use only built-in array methods (e.g., `_slice`, `_splice`) without relying on Lodash's utility functions.
* Introduce additional noise or variability into the benchmark by using different types of data structures (e.g., objects, matrices) or more complex operations.

Keep in mind that modifying these test cases may alter their accuracy and usefulness for measuring performance under specific scenarios.

Related benchmarks:

eestset (version: 0)

setstte

Comparing performance of: select vs slice

Created: 9 years ago by: Guest

Jump to the latest result

select

slice

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):