Benchmark: Test array - MeasureThat.net

Script Preparation code:

var array = new Array(1000000).fill(Math.random());

Tests:

1
const filtedArr = array.map(x => x % 2 === 0);
2
const filtedArr = [] for(const x of array) { if(x % 2 === 0) { filtedArr.push(x); } }
3
const filtedArr = array.filter(x => x % 2);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2
3

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.

I'll break down the provided benchmark test cases and explain what's being tested, compared, and considered.

**Benchmark Overview**

The test case measures the performance of three different approaches to filter an array of 1 million elements in JavaScript:

1. Using `Array.prototype.map()` with a callback function.
2. Using a traditional `for` loop to iterate over the array and push filtered elements into a new array.
3. Using `Array.prototype.filter()` with a callback function.

**Script Preparation Code**

The script preparation code generates an array of 1 million random numbers using `new Array(1000000).fill(Math.random())`.

**Individual Test Cases**

Each test case represents a separate benchmark:

1. **Test Case 1: Using `map()`**
```javascript
const filtedArr = array.map(x => x % 2 === 0);
```
This test case uses the `map()` method to create a new array with only even numbers from the original array.

**Test Case 2: Using Traditional Loop**

```javascript
const filtedArr = [];
for (const x of array) {
  if (x % 2 === 0) {
    filtedArr.push(x);
  }
}
```
This test case uses a traditional `for...of` loop to iterate over the original array and push filtered elements into a new array.

**Test Case 3: Using `filter()`**

```javascript
const filtedArr = array.filter(x => x % 2);
```
This test case uses the `filter()` method to create a new array with only numbers from the original array that satisfy the condition `x % 2`.

**Benchmark Results**

The latest benchmark results show the execution time (in executions per second) for each test case on a Chrome Mobile 92 browser, Android operating system, and mobile device.

**Comparison**

The tests compare the performance of three different approaches:

* **`map()`**: A concise and expressive way to filter an array.
* **Traditional Loop**: A more verbose approach that requires manual iteration and indexing.
* **`filter()`**: Another concise and expressive way to filter an array, similar to `map()`.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **`map()`**:
	* Pros: Concise, expressive, and easy to read.
	* Cons: May be slower due to the overhead of creating a new array.
2. **Traditional Loop**:
	* Pros: Can be faster for large arrays, as it avoids the overhead of creating a new array.
	* Cons: More verbose, harder to read, and error-prone.
3. **`filter()`**:
	* Pros: Concise, expressive, and easy to read.
	* Cons: May be slower than `map()` due to the additional overhead of filtering.

**Library and Special Features**

None of these test cases use any external libraries or special JavaScript features beyond the standard array methods (`map()`, `filter()`, and `for...of` loop).

**Other Alternatives**

If you're looking for alternative approaches, consider:

1. **Using a library**: There are many JavaScript libraries (e.g., Lodash) that provide additional filtering functions with optimizations.
2. **Using a Just-In-Time (JIT) compiler**: Some browsers and engines use JIT compilation to optimize performance-critical code.
3. **Using parallel processing or concurrency**: Modern JavaScript engines can take advantage of multi-core processors and asynchronous execution to improve performance.

Keep in mind that the best approach depends on your specific use case, performance requirements, and personal preference.

Related benchmarks:

Test array (version: 0)

Comparing performance of: 1 vs 2 vs 3

Created: 4 years ago by: Guest

Jump to the latest result

1

2

3

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):