Benchmark: for loop test brain

Script Preparation code:

var arr = [];
for (var i = 0; i < 12345; i++) {
  arr[i] = i;
}

function someFn(i) {
  return (i * 3 * 8 / 1200 * 0.002 / 40 * 0.2);
}

var sumForEach = 0,
  sumReduce = 0,
  sumMap = 0,
  sumFilter = 0,
  sumFor = 0;

Tests:

reduce
sumReduce = arr.reduce((lastValue, item) => { return lastValue + someFn(item); }, 0);
for
for (const item of arr) { sumFor += someFn(item); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
for

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):

LLMs can make mistakes. Check important info.

### Benchmark Overview

The benchmark being tested evaluates the performance of different methods for iterating through an array and applying a mathematical function to each element. The two specific approaches outlined in the benchmark are:

1. **Array.prototype.reduce()** method, which is a functional programming approach.
2. A traditional `for...of` loop, which is an imperative programming approach.

### Options Being Compared

1. **Reduce Method**:
   - **Test Case**: 
     ```javascript
     sumReduce = arr.reduce((lastValue, item) => {
       return lastValue + someFn(item);
     }, 0);
     ```
   - **Description**: `reduce` takes a callback function and accumulates a single value from the array’s items. In this case, it's summing the output of the `someFn` function when applied to each item in `arr`.

2. **For...of Loop**:
   - **Test Case**: 
     ```javascript
     for (const item of arr) {
       sumFor += someFn(item);
     }
     ```
   - **Description**: This loop iterates over each element in the array directly. Each element is passed to `someFn`, and the results are accumulated in `sumFor`.

### Pros and Cons of Each Approach

#### Array.prototype.reduce()

**Pros**:
- **Declarative Style**: It expresses the intention of accumulating values more clearly. It can lead to more readable code, especially for those familiar with functional programming.
- **Chaining**: `reduce` can be easily chained with other array methods (like `map`, `filter`), allowing for concise and versatile code design.

**Cons**:
- **Performance**: In some JavaScript engines, `reduce` can introduce overhead due to its abstraction and callback handling, potentially leading to slower execution times compared to loops.
- **Learning Curve**: Developers unfamiliar with functional programming concepts may need more time to grasp `reduce`.

#### For...of Loop

**Pros**:
- **Performance**: Typically, imperative loops like `for...of` can be faster since they are more direct and avoid the overhead associated with function calls in methods like `reduce`.
- **Simplicity**: For developers coming from other programming languages, classic loops may be more familiar and intuitive.

**Cons**:
- **Imperative Style**: It may lead to more verbose and less readable code, especially for more complex operations.
- **Less Flexible**: More challenging to compose with other functional operations due to the manual accumulation of results.

### Library and Special Features
- No external libraries are used in this benchmark; all functions and methods are part of the native JavaScript language.
- Additionally, `someFn` is a simple mathematical function that performs a fixed calculation. While not a JavaScript feature, understanding functions is fundamental in programming.

### Alternative Approaches
Other than `reduce` and `for...of`, several alternatives can be employed for similar tasks:

1. **Traditional For Loop**:
   ```javascript
   for (let i = 0; i < arr.length; i++) {
     sumFor += someFn(arr[i]);
   }
   ```
   This would typically be the fastest approach in most JavaScript engines, particularly for large datasets.

2. **ForEach Method**:
   ```javascript
   arr.forEach(item => {
     sumFor += someFn(item);
   });
   ```
   Similar to `reduce`, it expresses intent but doesn’t accumulate in a flexible way as `reduce` does. It also may be less performant than `for...of` loops.

3. **Map Method Combined with Reduce**:
   ```javascript
   sumMap = arr.map(someFn).reduce((acc, value) => acc + value, 0);
   ```
   This combines mapping the function over the elements and then reducing the result, but often comes with more overhead due to the creation of a new array.

### Conclusion
The choice between these different methods depends on specific requirements, including performance, readability, and familiarity. As seen from the benchmark results, `reduce` outperformed the `for...of` loop in this particular test, achieving a higher number of executions per second, illustrating that while theoretical benefits of clarity and expressiveness exist, real-world performance can vary significantly based on specific JS engine optimizations and implementation details.

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Linux

View result in a separate tab

Test name	Executions per second
reduce	2023.7 Ops/sec
for	707.0 Ops/sec

Related benchmarks:

for loop test brain (version: 0)

Comparing performance of: reduce vs for

Created: one month ago by: Guest

Jump to the latest result

reduce

for

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):