Benchmark: loop vs reduce for sums

Script Preparation code:

window.array = [];
for(let i = 0; i < 1000000; i++) {
  window.array.push(i);
}

Tests:

loop
let sum = 0; const array = window.array; for(let i = 0; i < array.length; i++) { sum += array[i]; }
reduce
window.array.reduce((acc, val) => acc + val );

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
loop
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36

Browser/OS: Chrome 85 on Mac OS X 10.15.6

View result in a separate tab

Test name	Executions per second
loop	946.2 Ops/sec
reduce	65.6 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 2 months 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 is defined in JSON format, which includes:

* `Name`: The name of the benchmark, "loop vs reduce for sums".
* `Description`: An empty string, indicating that no description is available.
* `Script Preparation Code`:
```javascript
window.array = [];
for(let i = 0; i < 1000000; i++) {
  window.array.push(i);
}
```
This code initializes an array of length 1,000,000 and assigns it to the global scope's `array` property. This means that both test cases will work with this pre-populated array.

* `Html Preparation Code`: An empty string, indicating no HTML preparation is needed.

**Individual Test Cases**

There are two test cases:

1. **Loop**:
```javascript
let sum = 0;
const array = window.array;
for(let i = 0; i < array.length; i++) {
  sum += array[i];
}
```
This code uses a traditional `for` loop to iterate over the `array` and calculate the sum.

2. **Reduce**:
```javascript
window.array.reduce((acc, val) => acc + val);
```
This code uses the built-in `reduce()` method of the Array prototype, which applies a callback function to each element in the array, accumulating a value that is returned as the result.

**Options Compared**

The benchmark compares two approaches:

* **Loop**: Uses a traditional `for` loop to iterate over the array.
* **Reduce**: Uses the built-in `reduce()` method of the Array prototype.

**Pros and Cons of Each Approach:**

1. **Loop**
	* Pros:
		+ Can be easier to understand for developers familiar with traditional loops.
		+ Allows for more control over iteration, such as skipping elements or modifying variables within the loop.
	* Cons:
		+ Can be slower due to the overhead of a `for` loop and potential indexing errors.
2. **Reduce**
	* Pros:
		+ Often faster than traditional loops since it leverages browser optimizations.
		+ More concise and expressive code.
	* Cons:
		+ May have performance issues if the callback function is complex or has side effects.
		+ Can be less intuitive for developers unfamiliar with functional programming concepts.

**Library Usage**

The `reduce()` method uses the Array.prototype, which is a built-in JavaScript library. The `Array` prototype provides a set of methods and properties that can be used to manipulate arrays, including `reduce()`, `push()`, `pop()`, `concat()`, and more.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntaxes mentioned in this benchmark. However, it's worth noting that the use of `window.array` suggests that this benchmark may be running in a browser environment, where variables in the global scope can affect performance and behavior.

**Other Alternatives**

For this type of benchmark, alternative approaches could include:

* Using other built-in methods, such as `forEach()` or `every()`, to iterate over the array.
* Implementing a custom iteration loop using `while` statements or recursive functions.
* Using a different data structure, such as an object or set, if applicable.

However, for this specific benchmark, the traditional `for` loop and `reduce()` method are the most relevant alternatives.

Related benchmarks:

loop vs reduce for sums (version: 0)

Comparing performance of: loop vs reduce

Created: 4 years ago by: Guest

Jump to the latest result

loop

reduce

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):