Benchmark: Reduce vs new arr creation.

Tests:

Reduce
var array = Array.from(Array(1000000).keys()); let newArr = array.reduce((acc, cur) => {acc.push(cur); return acc;}, [])
Push
var array = Array.from(Array(1000000).keys()); let newArr = []; array.forEach(x => newArr.push(x))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Reduce
Push

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definitions and explain what is being tested.

**Benchmark Definition:**

The test measures the performance difference between using `reduce()` and creating a new array by pushing elements into it.

**Options Compared:**

There are two main approaches being compared:

1. **Reduce()**: This method takes an initial value, iterates over an array, and applies a callback function to each element. The accumulator (acc) is returned at each step, and the final result is returned when the iteration finishes.
2. **Push() with Array.from() and forEach()**: This approach creates a new array using `Array.from()` and then uses the `forEach()` method to iterate over the original array, pushing elements into the new array.

**Pros and Cons of Each Approach:**

1. **Reduce():**
	* Pros:
		+ More memory-efficient since it doesn't create a new array.
		+ Can be more efficient for small arrays because it only needs to allocate space for the accumulator.
	* Cons:
		+ Requires an initial value, which might not always be available or desirable.
		+ Can lead to stack overflows if the callback function is too complex or deep in recursion.
2. **Push() with Array.from() and forEach():**
	* Pros:
		+ More intuitive and familiar for many developers, as it's similar to traditional array operations.
	* Cons:
		+ Creates a new array, which can be memory-intensive for large datasets.
		+ Can lead to more overhead due to the creation of a temporary array.

**Other Considerations:**

1. **Memoization:** Both approaches have potential for memoization to improve performance by caching results or intermediate values. However, this would require additional setup and might not always yield significant gains.
2. **Cache locality:** The reduce() approach tends to exhibit better cache locality due to the sequential nature of its execution.

**Library Usage:**

The benchmark doesn't explicitly use any external libraries. However, it does rely on JavaScript's built-in `Array.from()` method and the `forEach()` method, which are part of the ECMAScript standard.

**Special JS Features or Syntax:**

There is no special JavaScript feature or syntax being used in these benchmarks that would impact their interpretation for developers without deep knowledge of JavaScript. The use of ES6+ features like `Array.from()` and `reduce()` is widely adopted and should be familiar to most modern JavaScript developers.

**Alternatives:**

Other alternatives for creating a new array while pushing elements into it include:

1. **Using a for loop:** `for (let i = 0; i < arr.length; i++) { newArr.push(arr[i]); }`
2. **Using Array.prototype.map():** `newArr = arr.map(x => x);` (Note: This creates a new array, similar to `Array.from()`, but with more flexibility in mapping elements.)
3. **Using a library like Lodash:** `_.times(1000000, (_, i) => { newArr.push(i); });`

These alternatives have different trade-offs in terms of performance, memory usage, and code readability, which should be considered when choosing an approach for specific use cases.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36

Browser/OS: Chrome 103 on Windows

View result in a separate tab

Test name	Executions per second
Reduce	30.6 Ops/sec
Push	30.4 Ops/sec

Related benchmarks:

Reduce vs new arr creation. (version: 0)

Comparing performance of: Reduce vs Push

Created: 2 years ago by: Guest

Jump to the latest result

Reduce

Push

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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