Benchmark: foreach vs reduce

Script Preparation code:

dictionary = ['hack', 'a', 'rank', 'khac', 'ackh', 'kran', 'rankhacker', 'a', 'ab', 'ba', 'stairs', 'raits']
query = ["a", "nark", "bs", "hack", "stair"]

Tests:

reduce foreach filter
function name() { const sortedDictionary = dictionary.reduce((sorted, el) => { sorted.push(el.split('').sort().join('')) return sorted }, []) let count = 0 query.foreach(el => { sortedQuery = el.split('').sort().join('') count = sortedDictionary.filter(el => (el == sortedQuery).length) console.log(count) }) }
foreach foreach filter
function sorting(array) { let sortedArray = [] array.forEach((el) => { sortedArray.push(el.split('').sort().join('')) }) return sortedArray } function stringAnagram(dictionary, query) { // Write your code here let sortedDictionary = sorting(dictionary) let sortedQuery = sorting(query) let count=0 let counting=[] for (let i = 0; i < sortedQuery.length; i++) { count = sortedDictionary.filter((v) => (v === sortedQuery[i])).length; counting.push(count) } return counting }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce foreach filter
foreach foreach filter

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.6 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 16 on iOS 16.6.1

View result in a separate tab

Test name	Executions per second
reduce foreach filter	474495488.0 Ops/sec
foreach foreach filter	502913088.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark definition is a JSON object that describes two test cases:

1. `foreach vs reduce`: This test case compares the performance of two approaches:
	* `reduce` (Test Case 1): Uses the `Array.prototype.reduce()` method to sort an array of strings.
	* `forEach` (Test Case 2): Uses the `Array.prototype.forEach()` method in combination with a filter function to achieve similar results.

**Options Compared**

The benchmark compares the performance of two approaches:

1. **Reduce**: This approach uses the `reduce()` method to iterate over the array and perform the desired operation. It's often used when you need to process an array and return a single value.
2. **ForEach with filter**: This approach uses the `forEach()` method to iterate over the array, and then applies a filter function to extract the desired results.

**Pros and Cons**

**Reduce:**

Pros:

* Often more concise and expressive
* Can be more efficient for small arrays

Cons:

* May not perform well for large arrays or complex operations
* Can be less readable for some developers

**ForEach with Filter:**

Pros:

* More flexible and can handle complex operations
* Can be more readable for some developers

Cons:

* Often less concise than the `reduce()` approach
* May be slower for small arrays or simple operations

**Other Considerations**

In addition to these two approaches, it's worth noting that JavaScript also provides other methods for iterating over arrays, such as `Array.prototype.forEach()`, `Array.prototype.map()`, and `Array.prototype.filter()`. These methods may offer different trade-offs in terms of performance and readability.

**Test Case 1: Reduce**

The first test case uses the `reduce()` method to sort an array of strings. It then applies a filter function to extract the desired results. The code is concise and expressive, but it may not be immediately clear what's happening.

```javascript
function name() {
  const sortedDictionary = dictionary.reduce((sorted, el) => {
    sorted.push(el.split('').sort().join(''))
    return sorted
  }, [])

let count = 0
  query.foreach(el => {
    sortedQuery = el.split('').sort().join('')
    count = sortedDictionary.filter(el => (el == sortedQuery).length)
    console.log(count)
  })
}
```

**Test Case 2: ForEach with Filter**

The second test case uses the `forEach()` method in combination with a filter function to achieve similar results. The code is more verbose than the first test case, but it may be easier to understand for some developers.

```javascript
function sorting(array) {
  let sortedArray = []
  array.forEach((el) => {
    sortedArray.push(el.split('').sort().join(''))
  })
  return sortedArray
}

function stringAnagram(dictionary, query) {
  // Write your code here
  let sortedDictionary = sorting(dictionary)
  let sortedQuery = sorting(query)

let count = 0
  let counting = []

for (let i = 0; i < sortedQuery.length; i++) {
    count = sortedDictionary.filter((v) => (v === sortedQuery[i])).length;
    counting.push(count)
  }
  return counting
}
```

**Library Used**

In both test cases, the `forEach()` method is used, which is a built-in method of the `Array` object in JavaScript. No external libraries are required.

**Special JS Feature or Syntax**

There are no special features or syntax used in these examples that would require specific knowledge to understand.

**Other Alternatives**

In addition to the two approaches tested in this benchmark, there are other methods for iterating over arrays in JavaScript, such as:

* `Array.prototype.forEach()`: This method is similar to `forEach()` but doesn't return any value.
* `Array.prototype.map()`: This method applies a specified function to every element of an array and returns a new array with the results.
* `Array.prototype.filter()`: This method creates a new array with all elements that pass the test implemented by the provided function.

These methods may offer different trade-offs in terms of performance and readability, and should be considered when writing JavaScript code.

Related benchmarks:

foreach vs reduce (version: 0)

Comparing performance of: reduce foreach filter vs foreach foreach filter

Created: one year ago by: Guest

Jump to the latest result

reduce foreach filter

foreach foreach filter

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):