Benchmark: sum array - MeasureThat.net

Tests:

for
const input = [] for (let i = 0; i < 10000; i++) { input[i] = Math.floor(Math.random() * 10000) } let result = 0 for(let i = 0; i < input.length; i++) { result += input[i] } return result
forEach
const input = [] for (let i = 0; i < 10000; i++) { input[i] = Math.floor(Math.random() * 10000) } if(!input || !input.length) return 0 let result = 0 input.forEach(v => result + v) return result
reduce
const input = [] for (let i = 0; i < 10000; i++) { input[i] = Math.floor(Math.random() * 10000) } if(!input || !input.length) return 0 return input.reduce((a, b) => a+b);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for
forEach
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36

Browser/OS: Chrome 91 on Windows

View result in a separate tab

Test name	Executions per second
for	367.7 Ops/sec
forEach	336.9 Ops/sec
reduce	362.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of MeasureThat.net, a platform for creating and running JavaScript microbenchmarks.

**Benchmark Definition**

The provided benchmark definition is a JSON object that represents a simple JavaScript test case. It defines:

1. **Script Preparation Code**: None (empty string)
2. **Html Preparation Code**: None (empty string)

This means that the benchmark requires no setup code or HTML to prepare before running the test.

**Test Cases**

There are three individual test cases, each with its own `Benchmark Definition` and `Test Name`. The test cases are:

1. "for"
2. "forEach"
3. "reduce"

Each test case has a unique JavaScript function that calculates the sum of an array of random numbers.

**Options Compared**

The options compared in these test cases are:

* `for` loop
* `forEach` method
* `reduce` method

These three options are commonly used to iterate over arrays and perform calculations. The benchmark aims to measure their performance, efficiency, and execution speed.

**Pros and Cons of Different Approaches**

Here's a brief summary of the pros and cons of each approach:

1. **For Loop**
	* Pros: Simple, easy to understand, and widely supported.
	* Cons: Can be slower for large datasets due to the overhead of the loop control mechanism.
2. **ForEach Method**
	* Pros: Modern, concise, and efficient for many use cases.
	* Cons: May have performance issues when dealing with very large arrays or complex calculations.
3. **Reduce Method**
	* Pros: Efficient, modern, and widely supported (since ECMAScript 2015).
	* Cons: Can be less intuitive for beginners due to its abstract syntax.

**Library Usage**

None of the test cases use any external libraries. The `forEach` method is a built-in JavaScript method that doesn't rely on any third-party library.

**Special JS Features or Syntax**

The test cases don't explicitly use any special JavaScript features like async/await, generators, or closures. However, it's worth noting that the `for...of` loop (not used in these examples) and `const` declarations are relatively recent additions to the language and may be of interest.

**Alternatives**

Other alternatives for iterating over arrays and performing calculations include:

* Using `map()` and then reducing the result
* Utilizing libraries like Lodash or Ramda for more complex computations
* Leveraging modern JavaScript features like arrow functions, template literals, and spread operators

Keep in mind that these alternatives might not be as straightforward as using a simple `for` loop, but they can provide better performance and flexibility for certain use cases.

I hope this explanation helps you understand the MeasureThat.net benchmark and its test cases!

Related benchmarks:

sum array (version: 0)

Comparing performance of: for vs forEach vs reduce

Created: 3 years ago by: Guest

Jump to the latest result

for

forEach

reduce

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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