Benchmark: test-974 - MeasureThat.net

Script Preparation code:

const TYPE_AGENCE_ABBR = 'agence';
const TYPE_CONSTRUCTEUR_ABBR = 'constructor';
var menu = [{
        label: 'Personnaliser votre vitrine',
        to: '/vitrine/apercu/',
        forTypes: [TYPE_AGENCE_ABBR, TYPE_CONSTRUCTEUR_ABBR],
    },
    {
        label: 'Contenu de votre fiche agence',
        to: '/vitrine/fiche/',
        forTypes: [TYPE_AGENCE_ABBR, TYPE_CONSTRUCTEUR_ABBR],
    },
    {
        label: 'Gérer les adresses des agences',
        to: '/vitrine/gerer/',
        forTypes: [TYPE_AGENCE_ABBR, TYPE_CONSTRUCTEUR_ABBR],
    },
    {
        label: 'Créer vos modèles de maisons',
        to: '/vitrine/creer-modele/',
        forTypes: [TYPE_CONSTRUCTEUR_ABBR],
    },
    {
        label: 'Vos modèles de maisons',
        to: '/vitrine/modeles/',
        forTypes: [TYPE_CONSTRUCTEUR_ABBR],
    },
]

Tests:

filter map
menu.filter((tab) => tab.forTypes.some((type) => type === 'agence')).map((tab) => ({ title: tab.label, ...tab, active: tab.to === '', }))
reduce
menu.reduce((acc, { forTypes, ...tab }) => (forTypes.includes('some') ? [...acc, { title: tab.label, ...tab, active: tab.to === '', }] : acc ), [])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter map
reduce

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.

Let's break down the provided benchmark definition and explain what is being tested.

**Benchmark Definition:**

The benchmark consists of two individual test cases, each with its own definition in JSON format.

1. `filter map`:
```json
"Benchmark Definition": "menu.filter((tab) => tab.forTypes.some((type) => type === 'agence')).map((tab) => ({\r\n        title: tab.label,\r\n        ...tab,\r\n        active: tab.to === '',\r\n    }))"
```
This test case is testing the performance of the `filter` and `map` methods in JavaScript. The `menu` array contains objects with a `forTypes` property, which is an array of strings representing different types (e.g., 'agence' or 'constructor'). The test filters out the elements where `forTypes` includes 'agence', and then maps each remaining element to a new object with additional properties.

2. `reduce`:
```json
"Benchmark Definition": "menu.reduce((acc, { forTypes, ...tab }) => (forTypes.includes('some')\r\n        ? [...acc, {\r\n            title: tab.label,\r\n            ...tab,\r\n            active: tab.to === '',\r\n        }]\r\n        : acc\r\n    ), [])"
```
This test case is testing the performance of the `reduce` method in JavaScript. The `menu` array is being reduced, with each element processed as an object that has two properties: `forTypes` (an array of strings) and `tab` (the rest of the object). If `forTypes` includes 'some', a new object is created with additional properties and appended to the accumulator; otherwise, the accumulator remains unchanged.

**Options compared:**

In this benchmark, only two options are being compared:

1. **Filter + Map**: This option uses both `filter` and `map` methods to process the `menu` array.
2. **Reduce**: This option uses the `reduce` method to process the `menu` array.

**Pros and Cons:**

Here are some pros and cons of each approach:

**Filter + Map:**

Pros:

* Easy to understand and implement
* Flexible, as it allows for easy filtering and transformation of data

Cons:

* Can be slower due to the overhead of function calls and object creation

**Reduce:**

Pros:

* Efficient, as it reduces the number of iterations required to process the data
* Can be faster than filter + map for large datasets

Cons:

* Less intuitive for developers who are not familiar with reduce operations
* May require more memory to store the accumulator

**Other Considerations:**

* The use of `some` in the filter condition can lead to slower performance if the array is very large, as it requires iterating over each element.
* The use of spread operators (`...`) in both approaches can also introduce overhead.

**Library or Special JS Feature:**

There are no libraries or special JavaScript features explicitly mentioned in this benchmark. However, the use of `reduce` and `some` implies familiarity with functional programming concepts.

**Alternatives:**

Other alternatives to these two approaches could include:

* Using a library like Lodash or Underscore.js that provides additional utility functions for filtering and mapping data.
* Using a different data structure, such as an object graph, instead of an array.
* Optimizing the performance of each approach by using caching, memoization, or other optimization techniques.

Overall, this benchmark is testing the performance of two common JavaScript methods for processing arrays: `filter` + `map` and `reduce`. The results can help identify which approach is faster and more efficient for specific use cases.

Related benchmarks:

test-974 (version: 0)

Comparing performance of: filter map vs reduce

Created: 4 years ago by: Registered User

Jump to the latest result

filter map

reduce

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):