Benchmark: JS multiple function arguments vs. single arguments object

Script Preparation code:

var data = { a: 1, b: 2, c: 3, d: 4, e: 5, f: 6 };

function f1(a, b, c, d, e, f, g) {
  return a + b + c + d + e + f + g;
}

Tests:

Multiple arguments
f1(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
args object
f1({ a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random() })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Multiple arguments
args object

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 24 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Windows

View result in a separate tab

Test name	Executions per second
Multiple arguments	66183248.0 Ops/sec
args object	12942722.0 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided JSON represents a JavaScript microbenchmark that tests the performance of two different approaches to calling a function with multiple arguments: using individual positional arguments (`f1(a, b, c, d, e, f, g)`), and using an object with the same properties as the function's parameters (`f1({ a: data.a, b: data.b, c: data.c, d: data.d, e: data.e, f: data.f, g: Math.random() })`).

**Comparison of Options**

There are two main approaches being compared:

1. **Multiple arguments**: This approach uses individual positional arguments to call the function. The advantages of this approach include:
	* Readability and clarity of code
	* Easy maintenance and debugging
	* No need to create an object with specific property names
However, the disadvantages of this approach are:
	* Potential for typos or incorrect argument order
	* More verbose code when passing multiple arguments

2. **args object**: This approach uses an object with the same properties as the function's parameters to pass the arguments. The advantages of this approach include:
	* Reduced verbosity and easier maintenance
	* Less prone to typos or incorrect argument order
However, the disadvantages of this approach are:
	* Requires more explicit property names in the object
	* May be less readable for some developers

**Library Usage**

There is no library usage mentioned in the benchmark definition or test cases. However, it's worth noting that some libraries like Lodash or Ramda may provide utility functions that can help with creating objects or manipulating arrays, which could potentially impact performance.

**Special JS Features/Syntax**

There are a few special features and syntax used in this benchmark:

* The `Math.random()` function is used to generate a random value for the last argument (`g`) in both test cases. This ensures that the results are not deterministic.
* The `var` keyword is used to declare variables, which may impact performance or code readability depending on the context.

**Other Alternatives**

There are other alternatives to the two main approaches being compared:

* **Using an array**: Instead of using an object with specific property names, you could use an array and destructuring assignment to pass the arguments. For example: `f1([data.a, data.b, data.c, data.d, data.e, data.f, Math.random()])`.
* **Using a factory function**: You could create a factory function that generates an object with the required properties and passes it to the main function.

These alternatives may offer different trade-offs in terms of readability, maintainability, and performance. However, they are not explicitly mentioned in the benchmark definition or test cases.

Related benchmarks:

JS multiple function arguments vs. single arguments object (version: 0)

Comparing performance of: Multiple arguments vs args object

Created: 3 months ago by: Registered User

Jump to the latest result

Multiple arguments

args object

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):