Benchmark: set.has vs. array.includes (random string values), add strings not in list, smaller list

Script Preparation code:

var a = [
    'height',
    'width',
    'maxHeight',
    'maxWidth',
    'maxHeight',
    'minWidth',
    'color',
    'bg',
    'backgroundColor',
    'opacity',
    'm',
    'mt',
    'mb',
    'mr'
];
var b = new Set(a)

var c = a.slice();
c.push('abc','def','ghi','other word', 'notinlist','123','4334232313','borderwersese');

Tests:

arr.includes
return a.includes(c[Math.floor(Math.random() * c.length)])
set.has
return b.has(c[Math.floor(Math.random() * c.length)])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
arr.includes
set.has

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 JSON data and explain what's being tested, compared, and other considerations.

**Benchmark Definition**

The benchmark is designed to compare two JavaScript methods: `array.includes()` and `Set.has()`. The test aims to measure which method is faster for adding a string that is not in the list.

**Script Preparation Code**

The script prepares two arrays:

* `a`: an array of strings, including some duplicates.
* `c`: a copy of `a` with additional random strings added to it, including one string that is not in the original array (`'notinlist'`).

A new Set object `b` is created from the elements of array `a`.

**Html Preparation Code**

There is no HTML preparation code provided.

**Individual Test Cases**

The benchmark consists of two test cases:

1. `arr.includes`: This test case uses the `array.includes()` method to check if a random string from array `c` is present in array `a`.
2. `set.has`: This test case uses the `Set.has()` method to check if a random string from array `c` is present in Set object `b`.

**Options Compared**

The two methods are compared:

* `array.includes()`
* `Set.has()`

**Pros and Cons of Each Approach**

1. **Array Includes()**
	* Pros:
		+ Simple to implement.
		+ Fast for small arrays.
	* Cons:
		+ May not be optimized for larger arrays, leading to slower performance.
		+ May perform a linear search through the array, which can be slow for large datasets.
2. **Set.Has()**
	* Pros:
		+ Optimized for fast lookups in sets.
		+ Uses a hash table under the hood, making it efficient for large datasets.
	* Cons:
		+ May require additional memory overhead due to the set data structure.
		+ May have slower performance for small arrays or when adding elements is expensive.

**Other Considerations**

* **Memory Usage**: The benchmark may impact memory usage, especially if the array and Set objects are very large. This could affect system performance or lead to memory-related issues.
* **Cache Efficiency**: The benchmark's performance may be influenced by cache efficiency. For example, `Set.has()` might benefit from cache locality due to its hash table implementation.
* **Browser and Platform Variations**: The benchmark results may vary across different browsers, platforms, or versions due to differences in JavaScript engine optimizations, caching, and other factors.

**Library/Module Used**

The benchmark uses the built-in `Array` and `Set` objects, which are part of the ECMAScript standard. These objects provide optimized implementations for array and set operations, respectively.

**Special JS Feature/Syntax**

There is no specific JavaScript feature or syntax used in this benchmark that requires special explanation. The focus is on comparing two existing methods: `array.includes()` and `Set.has()`.

Related benchmarks:

set.has vs. array.includes (random string values), add strings not in list, smaller list (version: 0)

Comparing performance of: arr.includes vs set.has

Created: 5 years ago by: Guest

Jump to the latest result

arr.includes

set.has

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):