Benchmark: slice vs moving array vs reduce

Script Preparation code:

var arr = [];
for (var i = 0; i < 100; i++) {
  arr.push(i);
}

Tests:

moving array
var range = []; for (var i = 0; i < arr.length; i++) { range.push(arr[i]); if (range.length > 9) { range.splice(0, 1); } if (i > 8) {var avg = range.reduce(function(accu, next){ return accu + next ;}) / 9;} }
slice
for (var i = 0; i < arr.length; i++) { if (i < 9) continue; var range = arr.slice(i, i + 9); var avg = range.reduce(function(accu, next){ return accu + next ;}) / 9; }
reduce
var sum = 0; for (var i = 0; i < arr.length; i++) { sum += arr[i]; if (i > 8) { sum -= arr[i - 9]; } if (i > 8) {var avg = sum / 9;} }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
moving array
slice
reduce

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

**Overview of the Benchmark**

The provided JSON represents a JavaScript microbenchmarking test suite, which measures the performance of different approaches to calculate an average value from a slice of an array.

**Benchmark Definition**

The benchmark definition describes three test cases:

1. **"slice"**: This approach uses the `Array.prototype.slice()` method to extract a subset of elements from the original array.
2. **"moving array"**: This approach modifies the original array by removing elements and then calculates the average value using the reduced array.
3. **"reduce"**: This approach uses the `Array.prototype.reduce()` method to calculate the sum of the elements in the array and then divides it by 9 to get the average.

**Options Compared**

The benchmark compares the performance of three different approaches:

*   `slice()`: Uses the `Array.prototype.slice()` method to extract a subset of elements from the original array.
*   **Moving Array**: Modifies the original array by removing elements and then calculates the average value using the reduced array.
*   `reduce()`: Uses the `Array.prototype.reduce()` method to calculate the sum of the elements in the array and then divides it by 9 to get the average.

**Pros and Cons of Each Approach**

Here are some pros and cons of each approach:

1.  **`slice()`**: This approach is simple and efficient, but it may not be suitable for large arrays because it creates a new array object.
    *   Pros: Easy to implement, fast execution time.
    *   Cons: Creates a new array object, may consume more memory.
2.  **Moving Array**: Modifies the original array by removing elements before calculating the average value.
    *   Pros: Avoids creating a new array object, can be faster for large arrays.
    *   Cons: Modifies the original array, may have performance overhead due to repeated array modifications.
3.  **`reduce()`**: Uses the `Array.prototype.reduce()` method to calculate the sum of the elements in the array and then divides it by 9 to get the average.
    *   Pros: Efficient, avoids creating a new array object.
    *   Cons: May have performance overhead due to repeated array iterations.

**Library Used**

There is no explicit library used in this benchmarking test suite. However, `Array.prototype.slice()` and `Array.prototype.reduce()` are built-in JavaScript methods that operate on arrays.

**Special JS Features or Syntax**

This benchmarking test suite does not explicitly use any special JavaScript features or syntax like async/await, destructuring, or arrow functions.

**Alternatives**

If you're interested in exploring alternative approaches to this problem, here are some options:

1.  **Using `Array.prototype.map()`**: Instead of using `slice()`, you could use the `map()` method to create a new array with the desired subset of elements.
2.  **Using `Array.prototype.filter()`**: You could use the `filter()` method to remove unwanted elements from the original array before calculating the average value.
3.  **Using a custom implementation**: Instead of relying on built-in JavaScript methods, you could implement your own algorithm for calculating the average value from an array.

Keep in mind that each alternative approach may have its pros and cons, and some might be more efficient or suitable for specific use cases than others.

**Code Example**

Here's a simplified example code snippet demonstrating how to create an array with 100 elements using `for` loops and calculate the average value using each of the three approaches:
```javascript
var arr = [];
for (var i = 0; i < 100; i++) {
    arr.push(i);
}

// Using slice()
function calculateAverageSlice(arr, start, end) {
    var sum = 0;
    for (var i = start; i < end; i++) {
        sum += arr[i];
    }
    return sum / (end - start);
}

// Using moving array
function calculateAverageMovingArray(arr) {
    var sum = 0;
    var prevSum = 0;
    for (var i = 0; i < arr.length; i++) {
        if (i > 8) {
            prevSum -= arr[i - 9];
            if (prevSum <= 0) break;
        }
        sum += arr[i];
        if (sum >= 9) {
            return sum / 9;
        }
    }
}

// Using reduce()
function calculateAverageReduce(arr) {
    var sum = arr.reduce((accu, next) => accu + next, 0);
    return sum / 9;
}

var start = 8;
var end = 16;

console.log(calculateAverageSlice(arr, start, end));
console.log(calculateAverageMovingArray(arr.slice(start, end)));
console.log(calculateAverageReduce(arr.slice(start, end)));
```
This code snippet demonstrates how to calculate the average value from a subset of elements in an array using each of the three approaches.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Windows

View result in a separate tab

Test name	Executions per second
moving array	118351.0 Ops/sec
slice	131812.3 Ops/sec
reduce	112757.5 Ops/sec

Related benchmarks:

slice vs moving array vs reduce (version: 9)

Comparing performance of: moving array vs slice vs reduce

Created: 4 years ago by: Registered User

Jump to the latest result

moving array

slice

reduce

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):