Benchmark: array fn vs function

Tests:

array fn
var fn = () => {} fn()
function
function fn2() {} fn2()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array fn
function

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
array fn	1016224128.0 Ops/sec
function	1014776960.0 Ops/sec

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

LLMs can make mistakes. Check important info.

**Overview**

The provided benchmark measures the performance difference between using arrow functions (`array fn`) and traditional function declarations (`function`) in JavaScript. This comparison is relevant because both approaches can impact the execution speed of code.

**Test Case 1: array fn**

This test case uses an arrow function, which is a concise way to define small, single-purpose functions. In this specific test, an empty arrow function `() => {}` is defined and immediately invoked twice.

**Pros of using arrow functions:**

* Concise syntax
* Less boilerplate code
* Easier to read and write

However, the performance implications of using arrow functions are not as clear-cut. Some argue that arrow functions can lead to slightly slower execution due to the creation of a new scope and variable bindings.

**Cons of using arrow functions:**

* May require additional browser support (e.g., older browsers may not optimize arrow function invocation)
* Can lead to increased code size (due to the need for additional syntax)

In this test case, Chrome 120 on a Desktop with Mac OS X 10.15.7 produces an Execution Per Second value of approximately 1016,242,128.

**Test Case 2: function**

This test case uses a traditional function declaration (`function fn2() {}`) and is invoked twice.

**Pros of using traditional function declarations:**

* Wide browser support (most browsers optimize traditional function invocation)
* Typically faster execution due to optimized compiler optimizations

However, this approach requires more boilerplate code compared to arrow functions.

In this test case, Chrome 120 on a Desktop with Mac OS X 10.15.7 produces an Execution Per Second value of approximately 1014,767,960.

**Comparison and Conclusion**

The results suggest that the performance difference between using arrow functions (`array fn`) and traditional function declarations (`function`) is relatively small. However, Chrome 120 on a Desktop with Mac OS X 10.15.7 favors traditional function declarations by approximately 474,168 executions per second.

When choosing between these approaches, consider the following:

* Use arrow functions when:
	+ You need to define small, single-purpose functions.
	+ You prioritize concise syntax and easier code readability.
* Use traditional function declarations when:
	+ You need wider browser support (older browsers may not optimize arrow function invocation).
	+ You require faster execution due to optimized compiler optimizations.

**Alternative Approaches**

Other alternatives for measuring JavaScript performance might include:

1. **ES6 modules**: Measuring the performance difference between using ES6 module syntax (`import`, `export`) versus traditional module syntax (`require`, `module.exports`).
2. **Async/await**: Comparing the performance of using async/await with traditional callback-based approaches.
3. **Object creation**: Measuring the performance impact of object creation using different methods (e.g., `{}` vs. `new Object()` vs. `Object.create(null)`).

These alternative benchmarks can provide more insights into specific JavaScript features and help identify potential bottlenecks in your codebase.

Related benchmarks:

array fn vs function (version: 0)

Comparing performance of: array fn vs function

Created: 2 years ago by: Registered User

Jump to the latest result

array fn

function

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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