Benchmark: Testing - MeasureThat.net

Script Preparation code:

  function searchMostCommonNumber(arr) {
    if (arr === void 0) {
      arr = [];
    }
    var current = 0;
    var max = 0;
    var mostCommonNumber = 0;
    var i;
    for (i = 0; i < arr.length - 1; i++) {
      var current_1 = 1;
      var j = void 0;
      for (j = i + 1; j < arr.length; j++) {
        if (arr[i] === arr[j]) {
          current_1++;
        }
      }
      if (current_1 > max) {
        max = current_1;
        mostCommonNumber = arr[i];
      }
    }
    return mostCommonNumber;
  }


function mostCommonNumber(numbers) {
    let map = new Map()
    for (let num of numbers) {
        map.set(num, (map.get(num) || 0) + 1)
    }

    let mostCommonNumber = NaN
    let maxCount = -1
    for (let [num, count] of map.entries()) {
        if (count > maxCount) {
            maxCount = count
            mostCommonNumber = num
        }
    }

    return mostCommonNumber
}

numbers = Array(1e2).map(n => Math.floor(Math.random() * 1000))

Tests:

searchMostCommonNumber
searchMostCommonNumber(numbers)
mostCommonNumber
mostCommonNumber(numbers)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
searchMostCommonNumber
mostCommonNumber

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark and its options.

**Benchmark Definition JSON**

The benchmark definition is represented as a JavaScript function that calculates the most common number in an array of numbers. The function has two implementations:

1. `searchMostCommonNumber(arr)`: This function iterates through the array, counting the occurrences of each number. It keeps track of the maximum count and returns the corresponding number.
2. `mostCommonNumber(numbers)`: This function uses a Map data structure to count the occurrences of each number in the array. It then finds the key with the maximum value in the map.

**Options Compared**

The two functions are compared in terms of their performance, which is measured by the "ExecutionsPerSecond" metric. This metric represents how many times each function executes per second.

**Pros and Cons of Each Approach**

1. `searchMostCommonNumber(arr)`:
	* Pros: Simple, easy to understand, and doesn't require additional data structures.
	* Cons: Has a time complexity of O(n^2) due to the nested loop, making it less efficient for large arrays.
2. `mostCommonNumber(numbers)`:
	* Pros: Uses a more efficient data structure (Map) with a time complexity of O(n), making it faster than the first approach for large arrays.
	* Cons: Requires creating a Map object and potentially modifying its size, which can be slower due to memory allocation.

**Library/Functionality Used**

Both functions use JavaScript's built-in `Array` and `Math` objects. The second function also uses a `Map` object from the JavaScript Standard Library, which is available in modern browsers and Node.js environments.

**Special JS Feature/Syntax (Not Applicable)**

There are no special JavaScript features or syntax used in these benchmark functions.

**Other Alternatives**

Some alternative approaches could be:

* Using a different data structure, such as an object with numeric properties, to count the occurrences of each number.
* Utilizing a library like Lodash or Ramda, which provide optimized implementations for common array and mapping operations.
* Implementing a more efficient algorithm, such as counting only unique numbers and then finding the most common one.

Keep in mind that these alternatives may not be relevant to this specific benchmark and might require additional changes to the code.

Related benchmarks:

Testing (version: 4)

Comparing performance of: searchMostCommonNumber vs mostCommonNumber

Created: 8 years ago by: Registered User

Jump to the latest result

searchMostCommonNumber

mostCommonNumber

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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