Benchmark: ym0AIT7Il6askdakjdkakjsdkjb

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.17.21/lodash.min.js"></script>

Script Preparation code:

var arrFull = ['1','2','3','4','5','6','7','8','9','0']
var arrOne = ['2','4','5','7','8','9','0']

var set = new Set(['2','3','4','5','6','7']);

Tests:

Add passing
const passing = _.difference(arrOne, arrFull); passing.forEach(item => set.add(item))
Add all
arrOne.forEach(item => set.add(item))
Add all without anonymous arrow function
arrOne.forEach(set.add, set)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Add passing
Add all
Add all without anonymous arrow function

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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 and explain what is being tested, compared options, pros and cons of each approach, and other considerations.

**Benchmark Overview**

The benchmark measures the execution time of three different approaches to add elements from an array `arrOne` to a Set `set`. The array `arrFull` contains all possible values that can be added to the set, and the script preparation code initializes these arrays and sets up the test environment. The HTML preparation code includes a link to include the Lodash library, which provides the `difference` function used in one of the benchmark definitions.

**Test Cases**

There are three individual test cases:

1. **Add passing**: This test case uses the Lodash `difference` function to find elements that exist in `arrOne` but not in `arrFull`, and then adds these elements to the set using the `add` method.
2. **Add all**: This test case simply iterates over `arrOne` and adds each element to the set using the `add` method without any filtering or transformation.
3. **Add all without anonymous arrow function**: This test case uses a traditional for loop with a callback function to add elements to the set, instead of using an arrow function (i.e., `item => set.add(item)`).

**Comparison and Analysis**

The three test cases are compared in terms of their execution time on different browsers and devices.

| Test Case | Approach |
| --- | --- |
| Add passing | Uses Lodash `difference` function to filter elements, then adds using `add` method |
| Add all | Iterates over array and adds each element directly to the set using `add` method |
| Add all without anonymous arrow function | Traditional for loop with callback function |

**Pros and Cons of Each Approach**

1. **Add passing**:
	* Pros: Uses a efficient filtering approach, which can reduce the number of elements added to the set.
	* Cons: Requires including an external library (Lodash) and may have additional overhead due to the filtering step.
2. **Add all**:
	* Pros: Simple and straightforward implementation, no external libraries required.
	* Cons: May be slower than the other approaches due to the need to iterate over the entire array.
3. **Add all without anonymous arrow function**:
	* Pros: No additional library overhead, traditional for loop is a familiar pattern for many developers.
	* Cons: Less efficient than the other two approaches due to the need to iterate over each element individually.

**Other Considerations**

* The benchmark uses a fixed-size array `arrFull` and set `set`, which may not reflect real-world scenarios where data sizes can vary significantly.
* The test cases focus on the execution time of adding elements to a set, but do not consider other factors like memory usage or garbage collection overhead.

**Alternatives**

For measuring performance in JavaScript, you can also explore other tools and frameworks, such as:

1. **Benchmark.js**: A lightweight, modular benchmarking library for Node.js.
2. **Benchpress**: A high-performance benchmarking framework for Node.js.
3. **Speedtest**: A simple command-line tool for measuring execution time.

These alternatives offer different features and capabilities, so it's worth exploring each one to determine which best fits your specific needs.

Related benchmarks:

ym0AIT7Il6askdakjdkakjsdkjb (version: 0)

Comparing performance of: Add passing vs Add all vs Add all without anonymous arrow function

Created: 5 years ago by: Guest

Jump to the latest result

Add passing

Add all

Add all without anonymous arrow function

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):