Benchmark: twoja stara3 - MeasureThat.net

Script Preparation code:

var arr = [];

var createItem = function(group, value) {
  return {
    group: group,
    value: value
  }
}
const I = 12345
for (var i = 0; i < I; i++) {
  arr[i] = createItem('nosection', i);
}
arr[0] = createItem('section', 0);

Tests:

reduce
arr.reduce((acc, filter) => { if (filter.group === 'sections') acc.push(filter.value); return acc; }, []);
filter + map
arr.filter(_ => _.group === 'sections') .map(_ => _.value);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
filter + map

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.

I'll explain the benchmark and its results in detail.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmark, which allows users to create and run tests on specific code snippets. The benchmark is designed to compare the performance of two different approaches: `reduce` and `filter + map`.

**Script Preparation Code**

The script preparation code is a JavaScript function that creates an array of objects with two properties: `group` and `value`. The function `createItem` takes two arguments, `group` and `value`, and returns an object with these properties. The script also initializes an empty array `arr` and populates it with `I` number of elements using the `createItem` function. Finally, it sets the first element of the array to a different configuration.

**Html Preparation Code**

There is no HTML preparation code provided for this benchmark.

**Test Cases**

The benchmark consists of two test cases:

1. **"reduce"`**: This test case uses the `arr.reduce()` method to extract values from an array of objects, specifically those with a `group` property equal to `'sections'`.
2. **"filter + map"`**: This test case uses the `arr.filter()` and `map()` methods in combination to achieve the same result as the previous test case.

**Library Used**

There is no explicit library mentioned in the benchmark definition, but it appears that the `arr` array and its elements are assumed to be plain JavaScript objects. However, the use of the `reduce()` method suggests that the benchmark might be using a built-in JavaScript method or a polyfill for older browsers.

**Special JS Feature/Syntax**

The benchmark uses the arrow function syntax (e.g., `_ => _.group === 'sections'`) and template literals (e.g., `"arr.filter(_ => _.group === 'sections')"`). These features are supported in modern JavaScript environments, but if the benchmark is intended to run in older browsers or Node.js versions without these features, it may require polyfills or modifications.

**Benchmark Results**

The latest benchmark result shows two test cases with different performance characteristics:

1. **"filter + map"`**: This test case has a higher `ExecutionsPerSecond` value (9841.580078125) compared to the other test case.
2. **"reduce"`**: This test case has a lower `ExecutionsPerSecond` value (3438.839599609375).

The results suggest that, for this specific use case, using `filter + map` is faster than using `reduce`.

**Other Alternatives**

If you want to explore alternative approaches or optimizations for the same problem, consider the following:

* Using other array methods, such as `forEach()` or `every()`, might provide different performance profiles.
* Optimizing the script preparation code by reducing the number of elements created or using more efficient data structures could potentially improve performance.
* If you're targeting older browsers or Node.js versions without modern JavaScript features, consider using polyfills or alternative libraries to achieve similar results.

Related benchmarks:

twoja stara3 (version: 0)

Comparing performance of: reduce vs filter + map

Created: 6 years ago by: Guest

Jump to the latest result

reduce

filter + map

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):