Benchmark: Array.reduce vs for loop vs Array.forEachaaaa

Script Preparation code:

// Create an array of 1000 random intergers between 1 and 10000
var arrRandom = [];
for(var intCtr=0; intCtr<1000; intCtr++) {
  arrRandom.push(Math.floor(Math.random() * Math.floor(10000)));
}

function reduceCallback(accum, curr) {
	return accum+curr;
}

function doRedeuce(pArray) {
	return pArray.reduce(reduceCallback);
}
function doLoop(pArray) {
	var accum = 0;
	for(var intCtr=0; intCtr<pArray.length; intCtr++) {
		accum += pArray[intCtr];
	}
	return accum;
}
function doForEach(pArray) {
	var accum = 0;
	pArray.forEach(function(item) {
		accum += item;
	});
}
function doForOf(pArray) {
  var accum = 0;
  for(const intCtr of pArray) {
    	accum += intCtr
  }
  return accum
}

Tests:

reduce
var redeuceResult=0; redeuceResult = doRedeuce(arrRandom);
for loop
var loopResult=0; loopResult = doLoop(arrRandom);
forEach
var forEachResult=0 forEachResult = doForEach(arrRandom)
forOf
var forOfResult=0 forOfResult = doForOf(arrRandom)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
for loop
forEach
forOf

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark and explain what is tested, compared options, pros and cons, and other considerations.

**Benchmark Definition**

The benchmark measures the performance of three different approaches to summing 1000 random numbers:

1. `Array.reduce()`
2. Traditional `for` loop
3. `Array.forEach()` (with a callback function)
4. `for...of` loop

Each test case uses a slightly modified version of the same script preparation code, which generates an array of 1000 random integers between 1 and 10,000.

**Options Compared**

The benchmark compares the performance of the four approaches:

* **`Array.reduce()`**: Uses the `reduce()` method to sum up all elements in the array. The callback function takes two arguments: the accumulator (initially set to 0) and the current element.
* **Traditional `for` loop**: Iterates over the array using a traditional `for` loop, adding each element to the accumulator.
* **`Array.forEach()`**: Uses the `forEach()` method to iterate over the array, with a callback function that adds each element to the accumulator.
* **`for...of` loop**: Iterates over the array using a `for...of` loop, with the same callback function as in `Array.forEach()`.

**Pros and Cons**

Here are some pros and cons of each approach:

* **`Array.reduce()`**:
	+ Pros: Can be concise and expressive, especially for simple operations like summing elements.
	+ Cons: May have performance issues if the array is large or if the callback function is complex.
* **Traditional `for` loop**:
	+ Pros: Typically faster than the other three options, as it avoids the overhead of method calls.
	+ Cons: Can be verbose and less concise than other options.
* **`Array.forEach()`**:
	+ Pros: Similar to `reduce()`, but uses a more explicit iteration style.
	+ Cons: May have performance issues if the callback function is complex or if the array is large.
* **`for...of` loop**:
	+ Pros: Offers a concise and readable way to iterate over arrays, similar to `forEach()`.
	+ Cons: May be slower than traditional `for` loops due to its dynamic nature.

**Library**

None of these approaches use any external libraries. However, the `Array.forEach()` method does utilize the browser's built-in `Array.prototype.forEach()` implementation.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntaxes being tested in this benchmark. The tests focus on comparing different iteration styles and algorithmic approaches to summing elements.

**Alternatives**

If you're looking for alternative approaches to summing elements, consider the following:

* **Using a custom array function**: You can create a custom function that sums up all elements in an array using a combination of `for` loops or recursive functions.
* **Using a parallel processing approach**: If performance is critical, you might consider using parallel processing techniques like Web Workers to sum up multiple arrays concurrently.
* **Using a specialized library**: There are libraries like Lodash or Ramda that provide optimized implementations for various array operations, including summing elements.

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

Related benchmarks:

Array.reduce vs for loop vs Array.forEachaaaa (version: 0)

A test summing 1000 random numbers, 1 - 10000

Comparing performance of: reduce vs for loop vs forEach vs forOf

Created: 2 years ago by: Guest

Jump to the latest result

reduce

for loop

forEach

forOf

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):