Benchmark: Ayman 050523 - MeasureThat.net

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var max1 = 100000; // 100,000 (100 Thousand)
var max2 = 10000000; // 10,000,000 (10 Million)
var max3 = 100000000; // 100,000,000 (100 Million)

const strings = [
   'Uber* 12345',
   'Spark Fun',
   'Instacart',
]

var arr1 = _.times(max1, () => strings[_.random(0, 2)]);

var arr2 = _.times(max2, () => strings[_.random(0, 2)]);

var arr3 = _.times(max3, () => strings[_.random(0, 2)]);

Tests:

Only test case
arr1.filter((txn) => 'Instacart'.match(_.escapeRegExp(txn)))
bigger
arr2.filter((txn) => 'Instacart'.match(_.escapeRegExp(txn)))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Only test case
bigger

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.

**Overview**

The provided JSON represents a JavaScript microbenchmarking test case on the MeasureThat.net website. The test measures the performance of filtering an array in JavaScript using the `_.filter()` method with a regular expression.

**Benchmark Definition**

The benchmark definition consists of two individual test cases:

1. "Only test case": This test case filters an array containing three strings (`"Uber* 12345"`, `"Spark Fun"`, and `"Instacart"`) using the `_.escapeRegExp()` function, which escapes special characters in a string for use in a regular expression.
2. "bigger": This test case is similar to the first one, but with a larger array generated using `_times(max3, () => strings[_.random(0, 2)])`, where `max3` is set to 100 million.

**Options Compared**

The two test cases compare the performance of filtering an array in JavaScript. The difference lies in the size of the array being filtered:

* "Only test case" uses a smaller array with 100 thousand elements.
* "bigger" uses a larger array with 10 million elements.

**Pros and Cons of Different Approaches**

1. **Small array (100k elements)**:
	* Pros: Easier to generate and process, potentially more manageable for the JavaScript engine.
	* Cons: May not accurately represent real-world performance scenarios, as it's too small.
2. **Larger array (10 million elements)**:
	* Pros: More realistic representation of real-world performance scenarios, as it's closer to common use cases.
	* Cons: More challenging to generate and process, potentially requiring more memory and computational resources.

**Library**

The `_.` object is a part of the Lodash library, which provides various utility functions for working with arrays, objects, and strings. In this case, `_times()` generates an array by repeating a function execution a specified number of times, and `_filter()` applies a predicate to each element in the array, returning a new array with only the elements that pass the test.

**Special JS Features or Syntax**

This benchmark does not use any special JavaScript features or syntax beyond what's standard in modern JavaScript (ECMAScript 2015+).

**Other Considerations**

When running this benchmark, it's essential to note that:

* The `_.escapeRegExp()` function is used to escape special characters in the strings, which affects the performance of the filtering process.
* The `RawUAString`, `Browser`, `DevicePlatform`, and `OperatingSystem` fields provide metadata about the testing environment.
* The `ExecutionsPerSecond` value represents the average number of executions per second for each test case.

**Alternative Approaches**

Other alternatives to measure the performance of filtering an array in JavaScript might include:

* Using a different library or framework that provides similar functionality (e.g., `Array.prototype.filter()` with a custom regular expression).
* Measuring the performance of a specific use case, such as sorting or searching an array.
* Comparing the performance of different implementation strategies, such as using a hash table or a linear search.

Keep in mind that these alternatives might not accurately represent real-world scenarios or provide meaningful results for this particular benchmark.

Related benchmarks:

Ayman 050523 (version: 0)

Comparing performance of: Only test case vs bigger

Created: 3 years ago by: Guest

Jump to the latest result

Only test case

bigger

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):