Benchmark: Array.reduce vs for loops vs Array.forEach

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 doRedeuce(pArray) {
	return pArray.reduce(function(accum, curr) {
	    return accum+curr;
    });
}
function forLoop(pArray) {
	var accum = 0;
	for(var intCtr=0; intCtr<pArray.length; intCtr++) {
		accum += pArray[intCtr];
	}
	return accum;
}
function forOfLoop(pArray) {
	var accum = 0;
	for (var item of pArray) {
		accum += item;
	}
	return accum;
}
function doForEach(pArray) {
	var accum = 0;
	pArray.forEach(function(item) {
		accum += item;
	});
}

Tests:

reduce
var redeuceResult=0; redeuceResult = doRedeuce(arrRandom);
for loop
var loopResult=0; loopResult = forLoop(arrRandom);
forEach
var forEachResult=0 forEachResult = doForEach(arrRandom)
for-of loop
var loopResult=0; loopResult = forOfLoop(arrRandom);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
for loop
forEach
for-of loop

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its various components.

**Benchmark Definition:**
The benchmark is designed to compare the performance of three different methods for summing an array of numbers:

1. `Array.prototype.reduce()`
2. Traditional `for` loop
3. `Array.prototype.forEach()` with a callback function that adds up the values

These methods are commonly used in JavaScript for iterative calculations.

**Options Compared:**

*   `Array.prototype.reduce()`: This method uses an accumulator to keep track of the sum while iterating over the array.
*   Traditional `for` loop: This approach uses a manual index variable to iterate over the array and add up the values.
*   `Array.prototype.forEach()`: This method iterates over the array, but it doesn't return the accumulated value directly. A callback function is used to handle this.

**Pros and Cons of Each Approach:**

1.  **`Array.prototype.reduce()`**: This approach can be concise and expressive when used with higher-order functions.
    *   Pros: Efficient, easy to implement for large datasets.
    *   Cons: May not be optimal for very small arrays or arrays with non-numeric values.

2.  **Traditional `for` loop**:
    *   Pros: Easy to understand, can be optimized for performance in certain cases (e.g., using a fixed-size array).
    *   Cons: Can be verbose and error-prone, especially for large datasets.

3.  **`Array.prototype.forEach()`**: This approach can be convenient when used with callback functions.
    *   Pros: Easy to implement for simple use cases, handles errors well (by ignoring them).
    *   Cons: Not ideal for direct accumulation tasks, as it's designed for side effects rather than calculations.

**Library and Special Features:**

*   `Array.prototype.reduce()`: This is a built-in method in JavaScript. It uses an accumulator to reduce the array to a single value.
*   Traditional `for` loop and `Array.prototype.forEach()` don't rely on any external libraries or special features besides being part of the standard language.

**Alternative Approaches:**

1.  **`some()` and `every()` methods**: While not directly applicable for direct accumulation, these can be useful in more complex scenarios involving array filtering.
2.  **Generator functions**: These allow for more control over iteration and accumulation but come with a steeper learning curve.
3.  **Other libraries or frameworks**: Depending on the specific use case, other libraries (like jQuery) or frameworks might offer optimized implementations of these methods.

**Benchmark Result Explanation:**

The provided benchmark result shows the performance data for each method across different executions per second:

*   `Array.prototype.reduce()` performs best with a high execution rate (1207836.875).
*   Traditional `for` loop also delivers good results, but slightly lower than `reduce`. (883779.75)
*   Both `forEach` and `for-of loop` underperform compared to the other two approaches, although still within a reasonable range.

**Conclusion:**

When choosing between these methods for summing an array of numbers, consider factors such as code readability, performance requirements, and potential errors. For simple cases or when using higher-order functions, `Array.prototype.reduce()` is usually a good choice due to its efficiency and expressiveness. Traditional loops can be used for more control over iteration but come with their own set of trade-offs in terms of verbosity and optimization. `Array.prototype.forEach()` is less suitable for direct accumulation but can be convenient when working with callback functions.

Always remember that performance might vary based on the actual data being processed, so consider these factors when writing your benchmark code or choosing between methods.

Latest run results:

Run details: (Test run date: 2 days ago)

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 130 on Android

View result in a separate tab

Test name	Executions per second
reduce	268513.9 Ops/sec
for loop	490774.3 Ops/sec
forEach	553999.4 Ops/sec
for-of loop	681251.2 Ops/sec

Related benchmarks:

Array.reduce vs for loops vs Array.forEach (version: 0)

A test summing 1000 random numbers, 1 - 10000

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

Created: 3 years ago by: Guest

Jump to the latest result

reduce

for loop

forEach

for-of loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):