Benchmark: groupConsecutiveNumbers, large and small arrays

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

const reducerForGroupingConsecutiveNumbers = (accumulator, currentNumber, index) => {
  if (index === 0) {
    accumulator.push([currentNumber]);
  } else {
    const previousGroup = accumulator[accumulator.length - 1];
    const previousNumber = previousGroup[previousGroup.length - 1];
    if (currentNumber === previousNumber + 1 || currentNumber === previousNumber) {
      previousGroup.push(currentNumber);
    } else {
      accumulator.push([currentNumber]);
    }
  }
  return accumulator;
};

/**
 * Will create an array of subarrays of consecutive numbers
 * Given: [0,1,2,5,6,9];
 * Returns: [[0,1,2],[5,6],[9]]
 */
function createGroupingsOfConsecutiveNumbers(array) {
  return array.reduce(reducerForGroupingConsecutiveNumbers, []);
};

/** Groups consecutive input values, e.g. [1, 2, 4] -> [[1, 2], [4]] */
function groupConsecutiveNumbers(inputArray) {
  const initialValue = [[Number()]]; // Use a non-empty initial value to avoid edge cases: https://www.conjur.org/blog/special-cases-are-a-code-smell/
  const groupings = inputArray.reduce((accumulator, newNumber) => {
    /* last(accumulator) and last(last(accumulator)) will always be defined because
     * 1. its initial value is an array containing an array with at least one element and
     * 2. we never add array with fewer than 1 elements
     * They can therefore be safely casted as defined */
    const lastSubarray = _.last(accumulator);
    const lastNumber = _.last(lastSubarray);

    const isConsecutive = newNumber === lastNumber + 1 || newNumber === lastNumber;
    if (isConsecutive) {
      return [...accumulator.slice(0, -1), [...lastSubarray, newNumber]];
    }
    return [...accumulator, [newNumber]];
  }, initialValue);
  const [initialValueGroup, ...rest] = groupings;
  const withoutInitialValue = [initialValueGroup.slice(1), ...rest].filter((array) => array.length > 0);
  return withoutInitialValue;
}

Tests:

imperative (large arrays)
const numbersFromOneUpToTenThousandNotDivisibleByThree = [...Array(10000).keys()].filter(s => s % 3 !== 0); createGroupingsOfConsecutiveNumbers(numbersFromOneUpToTenThousandNotDivisibleByThree)
functional (large arrays)
const numbersFromOneUpToTenThousandNotDivisibleByThree = [...Array(10000).keys()].filter(s => s % 3 !== 0); groupConsecutiveNumbers(numbersFromOneUpToTenThousandNotDivisibleByThree)
imperative (small arrays)
const smallArray = [0, 1, 2, 5, 6, 9]; createGroupingsOfConsecutiveNumbers(smallArray)
functional (small arrays)
const smallArray = [0, 1, 2, 5, 6, 9]; groupConsecutiveNumbers(smallArray)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
imperative (large arrays)
functional (large arrays)
imperative (small arrays)
functional (small arrays)

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared options, pros and cons, and other considerations.

**Benchmark Overview**

The benchmark measures the performance of two functions: `createGroupingsOfConsecutiveNumbers` (imperative) and `groupConsecutiveNumbers` (functional). Both functions group consecutive numbers in an array. The benchmark tests these functions on small and large arrays, using both imperative and functional programming styles.

**What's being tested**

The benchmark measures the execution speed of the two functions:

1. **Imperative style**: `createGroupingsOfConsecutiveNumbers` uses a loop to iterate over the input array and group consecutive numbers.
2. **Functional style**: `groupConsecutiveNumbers` uses the `reduce()` method, which applies a reduction function to each element in the array.

**Comparison of options**

The benchmark compares two approaches:

1. **Imperative style**: The imperative approach uses a loop to iterate over the input array and group consecutive numbers.
2. **Functional style**: The functional approach uses the `reduce()` method, which applies a reduction function to each element in the array.

**Pros and Cons of each approach**

**Imperative style (createGroupingsOfConsecutiveNumbers)**

Pros:

* Easier to understand and debug for some developers
* Can be more efficient for small arrays or specific use cases

Cons:

* More verbose code
* May not be as scalable for large datasets

**Functional style (groupConsecutiveNumbers)**

Pros:

* Concise and expressive code
* Can be more scalable for large datasets
* Uses standard library functions, making it easier to maintain and update

Cons:

* May be less intuitive or harder to understand for some developers
* Can be slower due to the overhead of functional programming

**Other considerations**

* **Lodash**: The benchmark uses Lodash, a popular utility library that provides functions like `_.last()` and `_.reduce()`. These functions are used in the functional approach to group consecutive numbers.
* **Array methods**: Both approaches use array methods (e.g., `reduce()`) to process the input data. This choice of method can affect performance and readability.
* **Data size**: The benchmark tests both small and large arrays, which allows for a comparison of performance at different scales.

**Alternatives**

Other alternatives could include:

* Using a different programming paradigm (e.g., object-oriented instead of functional)
* Implementing the grouping logic from scratch without using standard library functions
* Using a different data structure or algorithm to group consecutive numbers

Keep in mind that these alternatives may not be as efficient, readable, or maintainable as the current implementation.

Related benchmarks:

groupConsecutiveNumbers, large and small arrays (version: 1)

Comparing performance of: imperative (large arrays) vs functional (large arrays) vs imperative (small arrays) vs functional (small arrays)

Created: 5 years ago by: Registered User

Jump to the latest result

imperative (large arrays)

functional (large arrays)

imperative (small arrays)

functional (small arrays)

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):