Benchmark: Javascript array deducplication 2.02

Script Preparation code:

var a = [1, 2, 3, 4, 5, 6, 5, 4];
var b = [6, 8, 2, 7, 6, 1, 4, 3];

function usingForEach(l1, l2) {
    let u = []

    l1.forEach(function(item) {
        if (u.indexOf(item) < 0)
            u.push(item);
    });

    l2.forEach(function(item) {
        if (u.indexOf(item) < 0)
            u.push(item);
    });

    return u;
};

function usingSet(l1, l2) {
    let u = l1.concat(l2); // Joins the l1 and l2 arrays together using concatenation.
    return [...new Set(u)]; // Array is converted into a 'Set' in order to remove duplicates, then is converted back into an array using the spread operator.
};

Tests:

forEach Test
var test1 = usingForEach(a,b);
usingSet Test
var test2 = usingSet(a,b);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach Test
usingSet Test

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 dive into the explanation of the provided benchmark.

**Benchmark Definition**

The benchmark is designed to measure the performance of two different approaches for removing duplicates from two arrays: `forEach` and `set`. The test case creates two sample arrays, `a` and `b`, and then defines two functions that use these arrays. One function uses the `forEach` method to iterate through both arrays and push unique items into a new array (`usingForEach`). The other function uses concatenation and then converting an array to a set using the spread operator to remove duplicates (`usingSet`).

**Options Compared**

The benchmark compares two options:

1. **Using `forEach`:** This approach iterates through both arrays, checks for uniqueness using `indexOf`, and pushes items into a new array if they don't exist.
2. **Using `set`:** This approach concatenates both arrays, converts the resulting array to a set, and then converts it back to an array using the spread operator.

**Pros and Cons of Each Approach**

1. **`forEach`:**
	* Pros:
		+ Can be more intuitive for developers familiar with iterating through arrays.
		+ Does not require converting between different data structures (arrays to sets).
	* Cons:
		+ May have performance issues due to the `indexOf` method being called repeatedly, leading to slower iterations.
		+ Can lead to unnecessary re-iterations of the same elements if they appear in both arrays multiple times.
2. **`set`:**
	* Pros:
		+ Generally faster and more efficient than using `forEach`, as it uses a hash-based data structure for set operations.
		+ Less prone to re-executing iterations, making it more suitable for large datasets.
	* Cons:
		+ Requires converting between arrays and sets, which can lead to additional overhead.
		+ May require additional libraries or functions (like `Set` in JavaScript) that might not be available in all environments.

**Library and Syntax**

The benchmark uses the `Set` data structure from the JavaScript standard library. This is a built-in data structure that stores unique values, making it suitable for removing duplicates.

There are no special JavaScript features or syntax used beyond what's already mentioned (using `forEach`, sets, etc.).

**Alternatives**

Other alternatives for removing duplicates from arrays include:

1. **Using `filter` and `includes`:**
	* Iterate through one array and use the other as a filter to exclude elements.
2. **Using `reduce`:**
	* Use the `reduce` method to iterate through both arrays, accumulating unique items into an accumulator array.

Keep in mind that these alternatives might have varying performance characteristics compared to using `set`.

Related benchmarks:

Javascript array deducplication 2.02 (version: 0)

electric boogaloo

Comparing performance of: forEach Test vs usingSet Test

Created: 3 years ago by: Guest

Jump to the latest result

forEach Test

usingSet Test

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):