Benchmark: Codewars outlier test

Script Preparation code:

var arr = new Array(1000000);
arr.fill(10);
arr[5] = 1

AخA
 
var arr = new Array(1000000);arr.fill(10);arr[5] = 1

Tests:

looping

function findOutlier(integers){
  //your code here
  var test;
  let i = 0;
  let len = integers.length;
  
  if ((integers[0] % 2 == 0 || integers[1] % 2 == 0) && (integers[2] % 2 == 0 || integers[3] % 2 == 0)) {
      // outlier is odd
      test = function(int) {
        return int % 2 !== 0;
      }
  } else {
      // outlier is even
      test = function(int) {
        return int % 2 === 0;
      }
  }
  
  for(i;i < len;i++) {
    if (test(integers[i])) {
      return integers[i]
    }
  }
    
}

findOutlier(arr);

​x
 
function findOutlier(integers){  //your code here  var test;  let i = 0;  let len = integers.length;    if ((integers[0] % 2 == 0 || integers[1] % 2 == 0) && (integers[2] % 2 == 0 || integers[3] % 2 == 0)) {      // outlier is odd      test = function(int) {        return int % 2 !== 0;      }  } else {      // outlier is even      test = function(int) {        return int % 2 === 0;      }  }    for(i;i < len;i++) {    if (test(integers[i])) {      return integers[i]    }  }    }​findOutlier(arr);​

filtering

function findOutlier(int){
  var even = int.filter(a=>a%2==0);
  var odd = int.filter(a=>a%2!==0);
  return even.length==1? even[0] : odd[0];
}

findOutlier(arr)

 
function findOutlier(int){  var even = int.filter(a=>a%2==0);  var odd = int.filter(a=>a%2!==0);  return even.length==1? even[0] : odd[0];}​findOutlier(arr)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
looping
filtering

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2025 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36

Browser/OS: Chrome 63 on Windows

View result in a separate tab

Test name	Executions per second
looping	4339432.5 Ops/sec
filtering	9.9 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

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

Benchmark Definition

The benchmark definition defines a JavaScript function findOutlier that takes an array of integers as input. The function is supposed to find the outlier in the array, which is the number that does not fit the pattern (either all even or all odd numbers).

Options Compared

There are two options being compared:

Looping: This option uses a traditional loop to iterate through the array and check each element against the test function.
Filtering: This option uses the filter() method to create two arrays, one for even numbers and one for odd numbers, and then returns the first element of the array with only one element.

Pros and Cons

Looping:
- Pros: Can be more straightforward to implement and understand.
- Cons: May be slower due to the overhead of the loop.
Filtering:
- Pros: Often faster and more concise, as it uses built-in methods that are optimized for performance.
- Cons: May be less intuitive or easier to debug, especially for those without experience with filter methods.

Library

None of the benchmarked code uses any external libraries. However, some browsers may have their own internal optimizations or implementation details that can affect the performance of the filter() method.

Special JS Features or Syntax

There are no special JavaScript features or syntax being used in this benchmark. The code is straightforward and uses standard JavaScript concepts.

Other Considerations

Array size: The benchmark uses an array of 1,000,000 elements, which can affect the performance differences between the two options.
Browser: The benchmark is run on a Windows machine with Chrome 63, but other browsers or platforms may have different performance characteristics.

Alternatives

Other alternatives for finding the outlier in an array include:

Using a mathematical approach, such as calculating the mean and then determining which number is not close to it.
Using a more advanced algorithm, such as the "outlier detection" algorithm used in some machine learning libraries.
Using a different data structure, such as a hash table or a trie.

However, these alternatives are likely to be slower or more complex than the simple filtering approach used in the benchmark.

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark definition defines a JavaScript function `findOutlier` that takes an array of integers as input. The function is supposed to find the outlier in the array, which is the number that does not fit the pattern (either all even or all odd numbers).

**Options Compared**

There are two options being compared:

1. **Looping**: This option uses a traditional loop to iterate through the array and check each element against the test function.
2. **Filtering**: This option uses the `filter()` method to create two arrays, one for even numbers and one for odd numbers, and then returns the first element of the array with only one element.

**Pros and Cons**

* **Looping**:
	+ Pros: Can be more straightforward to implement and understand.
	+ Cons: May be slower due to the overhead of the loop.
* **Filtering**:
	+ Pros: Often faster and more concise, as it uses built-in methods that are optimized for performance.
	+ Cons: May be less intuitive or easier to debug, especially for those without experience with filter methods.

**Library**

**Special JS Features or Syntax**

There are no special JavaScript features or syntax being used in this benchmark. The code is straightforward and uses standard JavaScript concepts.

**Other Considerations**

* **Array size**: The benchmark uses an array of 1,000,000 elements, which can affect the performance differences between the two options.
* **Browser**: The benchmark is run on a Windows machine with Chrome 63, but other browsers or platforms may have different performance characteristics.

**Alternatives**

Other alternatives for finding the outlier in an array include:

* Using a mathematical approach, such as calculating the mean and then determining which number is not close to it.
* Using a more advanced algorithm, such as the "outlier detection" algorithm used in some machine learning libraries.
* Using a different data structure, such as a hash table or a trie.

However, these alternatives are likely to be slower or more complex than the simple filtering approach used in the benchmark.

Related benchmarks:

Codewars outlier test (version: 0)

Comparing performance of: looping vs filtering

Created: 7 years ago by: Guest

Jump to the latest result