Benchmark: New set vs set clear 2

Script Preparation code:

const permSet = new Set()
for (let i = 0; i < 100; i++) {
  permSet.add(Math.floor(Math.random() * 100000));
}

Tests:

new set
permSet = new Set()
clear set
const arr = [...permSet] permSet.clear()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
new set
clear set

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36

Browser/OS: Chrome 112 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
new set	6751929.5 Ops/sec
clear set	6424931.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the benchmark and explore what's being tested.

**Benchmark Overview**

The benchmark, titled "New set vs set clear 2", measures the performance difference between creating a new Set instance and clearing an existing one in JavaScript.

**Test Cases**

There are two test cases:

1. **"new set"`**: This test case creates a new Set instance using the expression `const permSet = new Set()`. The script preparation code is provided, which populates the set with 100 random numbers.
2. **"clear set"`**: This test case clears an existing Set instance by first creating a Set instance and then adding some elements to it (`const arr = [...permSet]`). After that, it calls `permSet.clear()`. The script preparation code is provided as well.

**Comparison of Options**

The benchmark compares two approaches:

1. **Creating a new Set instance**: This approach involves allocating memory for a new Set object, which requires some overhead.
2. **Clearing an existing Set instance**: This approach involves copying the elements from the original Set instance to a temporary array (`const arr = [...permSet]`), and then clearing the original Set instance.

**Pros and Cons of Each Approach**

1. **Creating a new Set instance**:
	* Pros: More efficient in terms of memory allocation, as it doesn't require copying existing data.
	* Cons: Requires more overhead to create a new object, which might impact performance in some cases.
2. **Clearing an existing Set instance**:
	* Pros: Faster and more efficient, as it only requires copying the elements from the original Set instance to a temporary array.
	* Cons: Requires more memory allocation, as it needs to store the copied data.

**Library Used**

The benchmark uses the `Set` object, which is a built-in JavaScript data structure. The `Set` object provides an efficient way to store unique values, and its methods (e.g., `add()`, `clear()`) are optimized for performance.

**Special JS Feature or Syntax**

There's no specific JavaScript feature or syntax being tested in this benchmark. However, it's worth noting that the use of a Set object is a built-in JavaScript feature, which makes this benchmark more focused on measuring the performance difference between creating and clearing a set versus an array.

**Other Alternatives**

If you wanted to test alternative approaches, here are some possibilities:

1. Using `Array.prototype.push()` instead of `Set.prototype.add()`: This would simulate adding elements to an array using push.
2. Using a custom data structure, such as a linked list or a tree data structure: These alternatives would require more complex implementation and testing.
3. Using a different language or implementation (e.g., Rust, C++): This would allow you to compare the performance of JavaScript with other languages.

Keep in mind that these alternative approaches might not accurately represent real-world use cases or scenarios.

Related benchmarks:

New set vs set clear 2 (version: 0)

Comparing performance of: new set vs clear set

Created: one year ago by: Guest

Jump to the latest result

new set

clear set

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):