Benchmark: branched single/empty

Script Preparation code:

function sumBasic(numbers) {
  let sum = 0;
  for (const number of numbers) {
    sum += number;
  }
  return sum;
}

function sumBranched(numbers) {
  let sum = 0;
  if (Array.isArray(numbers)) {
    for (const number of numbers) {
      sum += number;
    }
  } else if (numbers !== undefined) {
    sum = numbers;
  }
  return sum;
}

var singleArray = [10];
var emptyArray = [];
var largeArray = [...Array(1000).keys()];

Tests:

basic empty
sumBasic(emptyArray);
branched empty
sumBranched(undefined);
basic single
sumBasic(singleArray);
branched single
sumBranched(10);
basic large
sumBasic(largeArray);
branched large
sumBranched(largeArray);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
basic empty
branched empty
basic single
branched single
basic large
branched large

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's dive into the world of MeasureThat.net!

**Benchmark Definition JSON**

The provided JSON defines a benchmark for testing the performance of JavaScript functions. Here's what's being tested:

* The `sumBasic` function is a basic implementation of the sum function, which takes an array of numbers as input and returns their sum.
* The `sumBranched` function is an alternative implementation of the sum function that uses branching logic to handle different input types (array, number, or undefined).

**Comparison Options**

There are two comparison options being tested:

1. **Basic Sum**: This option tests the `sumBasic` function with an empty array (`emptyArray`) as input.
2. **Branched Sum**: This option tests the `sumBranched` function with both an empty array (`emptyArray`) and a single number (10) as input.

**Pros and Cons of each approach**

* **Basic Sum**:
	+ Pros: Simple to implement, easy to understand, and should provide a good baseline for comparison.
	+ Cons: May not be optimized for performance, especially with large input arrays.
* **Branched Sum**:
	+ Pros: Can handle different input types more efficiently than the basic sum approach. However, it may introduce additional overhead due to the branching logic.
	+ Cons: More complex implementation, potentially harder to understand and debug.

**Library usage**

The `Array.isArray()` function is used in both functions to check if the input is an array. This function is a built-in JavaScript method that returns `true` if the input is an array and `false` otherwise.

**Special JS feature or syntax**

There are no special features or syntaxes being tested here, as this is a basic benchmark for comparing the performance of two simple functions.

**Other alternatives**

If you want to test other variations of these functions, you could consider adding more options, such as:

* Using `some()` instead of `for` loops
* Using `map()` instead of iterating over each element manually
* Using `reduce()` instead of manual summing
* Testing with different input sizes (e.g., small arrays, large arrays, etc.)

Keep in mind that adding more options can make the benchmark more complex and potentially harder to understand. MeasureThat.net's approach is well-suited for simple, straightforward benchmarks like this one.

To prepare a new benchmark using this JSON structure, you would create a new `Benchmark Definition` with your own functions and test cases. Then, simply update the results array with the performance data for each test case.

Related benchmarks:

branched single/empty (version: 0)

Comparing performance of: basic empty vs branched empty vs basic single vs branched single vs basic large vs branched large

Created: 3 years ago by: Guest

Jump to the latest result

basic empty

branched empty

basic single

branched single

basic large

branched large

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):