Benchmark: Find the outlier number

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

/*your preparation JavaScript code goes here
To execute async code during the script preparation, wrap it as function globalMeasureThatScriptPrepareFunction, example:*/
async function globalMeasureThatScriptPrepareFunction() {
    // This function is optional, feel free to remove it.
    // await someThing();
}

/*
findOutlier([1,3,5,7,9,11,13,15,2]);
findOutlier2([1,3,5,7,9,11,13,15,2]);
*/

function findOutlier(integers){
  odd = [];
  even = [];
  outlier = -1;
  
  for (let x = 0; x < integers.length; x++) {
    let num = integers[x]; 
    if(num % 2 === 0 || num === 0) {
      odd.push(num);
    } else {
      even.push(num);
    }
    
    if(integers.length - 1 === x) {
      outlier = Number((odd.length === 1) ? odd : even);
    }
  }
  
  return outlier;
}

function findOutlier2(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];
}

Tests:

Test1
findOutlier2([2, 4, 0, 100, 4, 11, 2602, 36])
Test2
findOutlier([2, 4, 0, 100, 4, 11, 2602, 36])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Test1
Test2

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36 Edg/133.0.0.0

Browser/OS: Chrome 133 on Windows

View result in a separate tab

Test1

20.6M/s

Test2

5.6M/s

View exact numbers

Test name	Executions per second
✓ Test1	20,590,990 Ops/sec
Test2	5,608,173 Ops/sec

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

LLMs can make mistakes. Check important info.

The benchmark titled "Find the Outlier Number" performs performance comparisons between two different implementations of a function designed to identify an outlier in a collection of numbers - specifically, the number that differs from the majority of others in terms of being odd or even.

### Options Compared

1. **findOutlier(integers) Function**
    - This implementation iterates through the given array of integers, separating them into two categories: odd and even numbers, using a `for` loop. It keeps track of both categories and determines the outlier by checking which category contains a single element at the end of the iteration. 
    - **Pros**:
        - Straightforward logic that uses simple loops and conditionals; easy to understand.
        - Only iterates through the list once, maintaining a constant space with just two arrays.
    - **Cons**:
        - Slightly less efficient in terms of performance as it constructs two temporary arrays and only checks for the outlier on the final iteration which may involve unnecessary comparisons.

2. **findOutlier2(int) Function**
    - This implementation utilizes the JavaScript `filter` method to create two filtered arrays (one for even numbers and one for odd) and then immediately returns the single element from the category that contains only one number.
    - **Pros**:
        - More concise and functional programming style which can be easier to read and maintain.
        - Takes advantage of JavaScript’s array methods for clearer and often more optimized operations written directly in a single line.
    - **Cons**:
        - Involves creating two new arrays, which increases memory overhead, especially with large datasets.
        - May be less efficient in terms of time complexity due to the need to traverse the list multiple times (once for each filter).

### Additional Considerations

- **Performance Benchmarking**: The tests output specific metrics for executions per second for each function when executed with the same array of inputs.
    - **Executions Per Second**:
        - `findOutlier2`: 5,608,173 calls per second.
        - `findOutlier`: 20,590,990 calls per second.
    - The results clearly show that `findOutlier` outperforms `findOutlier2` in this specific case by a large margin, indicating a far better performance in handling the same input size when measured.

### Alternatives

- Alternatives to the methods being measured can include:
    - A single-pass solution that avoids using additional arrays by simply counting the odd and even numbers and determining the outlier in one go. This could be implemented with a tracking counter and potentially more complex conditional logic but would likely lead to lower memory usage.
    - Utilizing mathematical properties or statistical approaches to determine the outlier without explicitly categorizing elements.
    - Code that utilizes more advanced data structures, such as objects or maps, to track counts, may offer additional optimizations depending on the situation.

In conclusion, the benchmark showcases a basic exercise that not only tests the efficiency of two different approaches to solving the same problem but also illustrates the trade-offs between readability, maintainability, and performance within JavaScript programming. Both implementations have their place, contingent upon context and specific use cases, but the results provide a strong argument for the performance advantages of the first method in this instance.

Find the outlier number (version: 1)

Comparing performance of: `Test1 vs Test2`

Created: one year ago by: Guest

Go to the latest result

Test1

Test2

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Find the outlier number (version: 1)

Comparing performance of: Test1 vs Test2

Created: one year ago by: Guest

Go to the latest result

Test1

Test2

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Comparing performance of: `Test1 vs Test2`