Benchmark: set.has vs. array.includes vs array.find vs map.has (20 elements)

Script Preparation code:

var a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20];
var b = new Set(a)
var c = new Map();
a.forEach(x => c.set(x, x)) // just for test.

Tests:

Array.includes
return a.includes(19)
Set.has
return b.has(19)
Array.find
return a.find(x => x === 19)
Map.has
return c.has(9)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.includes
Set.has
Array.find
Map.has

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark is designed to compare the performance of different methods for checking if an element exists in arrays and sets. The test case includes four scenarios:

1. `Array.includes`
2. `Set.has`
3. `Array.find` (although this method typically returns the found element, not a boolean indicating existence)
4. `Map.has`

**What's being tested**

The benchmark measures the execution time of each method for checking if an element exists in the specified array or set.

**Options Compared**

1. **Array.includes**: This method searches the entire array to find the specified element.
2. **Set.has**: This method uses a hash table to quickly check if an element is present in the set.
3. **Array.find**: Although this method typically returns the found element, the benchmark measures its execution time for checking existence.
4. **Map.has**: Similar to Set.has, this method uses a hash table to quickly check if an element is present in the map.

**Pros and Cons**

1. **Array.includes**:
	* Pros: Easy to implement, intuitive.
	* Cons: Slow for large arrays, inefficient use of resources.
2. **Set.has**:
	* Pros: Fast, efficient, suitable for large datasets.
	* Cons: Requires creating a set, which can be memory-intensive.
3. **Array.find**:
	* Pros: Returns the found element, easy to implement.
	* Cons: Slow for checking existence only, inefficient use of resources.
4. **Map.has**:
	* Pros: Fast, efficient, suitable for large datasets.
	* Cons: Requires creating a map, which can be memory-intensive.

**Library and Special JS Features**

1. `Set` and `Map` are built-in JavaScript objects that provide efficient data structures for storing and retrieving elements.
2. The `Array.find()` method was introduced in ECMAScript 2015 (ES6) and provides a way to find the first element in an array that satisfies a provided condition.

**Other Considerations**

When choosing between these methods, consider the size of your dataset, the frequency of lookups, and any additional requirements (e.g., returning the found element).

Alternative approaches include:

1. **Using `in` operator**: This can be faster than `includes()` for checking existence in arrays.
2. **Using a custom implementation**: Depending on the specific use case, you might be able to optimize the lookup process using a custom algorithm or data structure.

Keep in mind that these alternatives may not be as straightforward to implement as the methods tested by the benchmark.

Latest run results:

Run details: (Test run date: 11 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.5993.821 YaBrowser/23.11.2.821 Yowser/2.5 Safari/537.36

Browser/OS: Yandex Browser 23 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Array.includes	27949182.0 Ops/sec
Set.has	27225324.0 Ops/sec
Array.find	22223546.0 Ops/sec
Map.has	23196666.0 Ops/sec

Related benchmarks:

set.has vs. array.includes vs array.find vs map.has (20 elements) (version: 0)

Comparing performance of: Array.includes vs Set.has vs Array.find vs Map.has

Created: 11 months ago by: Guest

Jump to the latest result

Array.includes

Set.has

Array.find

Map.has

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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