Benchmark: for vs forEach - MeasureThat.net

Script Preparation code:

var testArray = [];

for (var i = 1; i <= 1000; i++) {
   testArray.push(i);
}

Tests:

for loop
for(var i = 0, length = testArray.length; i < length; i += 1) { testArray[i] += 1; }
forEach
testArray.forEach((item) => { item += 1; });
Map
testArray.map((item) => { item += 1; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for loop
forEach
Map

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark definition is an object that defines the test scenario. In this case, it specifies three different approaches:

1. **For Loop**: This option uses a traditional for loop to iterate over an array and increment each element.
2. **ForEach**: This option uses the `forEach` method to iterate over an array and increment each element.
3. **Map**: This option uses the `map` method to create a new array with the same elements, but with each element incremented.

**Options Compared**

The benchmark is comparing the performance of these three approaches:

* For Loop: Iterates over the array using a traditional loop, incrementing each element manually.
* ForEach: Iterates over the array using the `forEach` method, which is designed for iterating over arrays and modifying elements in place.
* Map: Creates a new array with the same elements, but with each element incremented.

**Pros and Cons**

Here are some pros and cons of each approach:

* **For Loop**: Pros:
	+ Can be more intuitive and easier to understand for those familiar with traditional loops.
	+ Allows for manual control over the iteration process.
Cons:
	+ Can be slower due to the overhead of manually incrementing elements.
* **ForEach**: Pros:
	+ Designed specifically for iterating over arrays, making it efficient and concise.
	+ Reduces boilerplate code compared to a traditional loop.
Cons:
	+ May not be as intuitive for those unfamiliar with `forEach`.
	+ Can lead to issues if the array is modified while iterating (e.g., using `push` or `splice`).
* **Map**: Pros:
	+ Creates a new array, which can simplify the iteration process and avoid modifying the original array.
Cons:
	+ Requires creating a new array, which can be slower than incrementing elements in place.
	+ May lead to increased memory usage.

**Library**

None of the benchmark options use any external libraries. The `forEach` and `map` methods are built-in methods of the Array prototype in JavaScript.

**Special JS Feature or Syntax**

The benchmark does not use any special JavaScript features or syntax beyond what is built-in to the language.

**Other Considerations**

When choosing between these approaches, consider the trade-offs between performance, conciseness, and maintainability. For simple iterations over arrays, `forEach` may be a good choice due to its efficiency and simplicity. However, for more complex scenarios or when manual control is required, a traditional loop like the **For Loop** option may be more suitable.

Other alternatives to consider:

* **Reduce**: Another array method that can be used for iterating over arrays.
* **Filter**: An array method that can be used for filtering elements in an array.
* **Closures**: A feature of JavaScript that allows creating private, encapsulated variables and functions.

Latest run results:

Run details: (Test run date: 2025 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.140 Safari/537.36

Browser/OS: Chrome 64 on Windows

View result in a separate tab

Test name	Executions per second
for loop	7500.7 Ops/sec
forEach	326298.2 Ops/sec
Map	196358.6 Ops/sec

Related benchmarks:

for vs forEach (version: 0)

Comparing performance of: for loop vs forEach vs Map

Created: 6 years ago by: Guest

Jump to the latest result

for loop

forEach

Map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):