Benchmark: Loop vs Recursion for Array

Script Preparation code:

var DogArr = [ "Great Pyranees", "Great Dane", "Irish Wolfhound", "Golden Retriever" ];

function runLoop() {
	for( var i = 0; i < DogArr.length; i++ )
    {
    	console.log( DogArr[ i ] );
    }
  	return;
}

function runRecursion() {
  	var count = 0;
	function loopThroughArray() {
    	if( count < DogArr.length ) {
          console.log( DogArr[ count ] );
          loopThroughArray();
        } else {
        	return;
        }
      
    }

}

Tests:

Loop
runLoop();
Recursion
runRecursion();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Loop
Recursion

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Linux; Android 8.1.0) AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/79.0.3945.136 Mobile Safari/537.36 DuckDuckGo/5

Browser/OS: Chrome Mobile 79 on Android 8.1.0

View result in a separate tab

Test name	Executions per second
Loop	2782.0 Ops/sec
Recursion	1041711.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down what is being tested in the provided benchmark.

The benchmark compares two approaches to iterate over an array:

**Approach 1: Loop**

The `runLoop` function uses a traditional `for` loop to iterate over the elements of the `DogArr` array. The loop variable `i` starts from 0 and increments until it reaches the length of the array.

**Approach 2: Recursion**

The `runRecursion` function uses recursion to iterate over the elements of the `DogArr` array. The `loopThroughArray` inner function calls itself with an incremented counter `count` until it reaches the length of the array.

Now, let's discuss the pros and cons of each approach:

**Loop:**

Pros:

* Generally faster and more efficient, as it avoids the overhead of recursive function calls.
* Can be optimized for specific use cases, such as using `for...of` or `forEach` loops.

Cons:

* May not be suitable for all types of data, such as arrays with large numbers of elements that don't fit in memory.
* Can lead to stack overflows if the recursion depth is too high.

**Recursion:**

Pros:

* Can be more concise and easier to understand for some developers.
* Can be used to implement complex logic or tree traversals.

Cons:

* Generally slower and less efficient than loops, due to the overhead of recursive function calls.
* Can lead to stack overflows if the recursion depth is too high.
* May not be suitable for large datasets that don't fit in memory.

Other considerations:

* The benchmark uses a relatively small array size (4 elements), which may affect the results. Larger arrays might favor one approach over the other.
* The `runRecursion` function uses a variable `count` to keep track of the iteration, whereas the `runLoop` function uses the `i` loop variable directly. This might impact performance depending on the specific use case.

As for the libraries used in this benchmark, none are explicitly mentioned. However, it's worth noting that the `console.log()` statement is a built-in Node.js function, and the `var` keyword is used to declare variables (although not recommended in modern JavaScript).

There aren't any special JS features or syntax mentioned in the provided code.

For alternative approaches, here are some options:

* **Iterators**: Instead of using traditional loops or recursion, you could use iterators to iterate over arrays.
* **Generators**: You could use generators to implement recursive-like behavior without the overhead of function calls.
* **Parallel processing**: If the array size is very large, parallel processing techniques like worker threads or parallel.js might be worth exploring.

Keep in mind that the best approach depends on the specific requirements and constraints of your project.

Related benchmarks:

Loop vs Recursion for Array (version: 0)

Comparing performance of: Loop vs Recursion

Created: 8 years ago by: Guest

Jump to the latest result

Loop

Recursion

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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