Benchmark: JS multiple parameters vs parameter object 2

Script Preparation code:

var data = { a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: 7 }

function f1(a, b, c, d, e, f, g) {
  return a + b + c + d + e + f + g;
}

function f2(p) {
  return p.a + p.b + p.c + p.d + p.e + p.f + p.g;
}

Tests:

Multiple parameters
f1(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
Existing parameter object
data.g = Math.random(); f2(data)
Parameter object with spreading
f2({ ...data, g: Math.random() })
New parameter object
f2({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Multiple parameters
Existing parameter object
Parameter object with spreading
New parameter object

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

The provided benchmark definition json represents a set of test cases for measuring the performance difference between various approaches to passing arguments to a function in JavaScript. The main functions being compared are `f1` and `f2`.

**Function f1**

`f1` is a simple function that takes 7 parameters: `a`, `b`, `c`, `d`, `e`, `f`, and `g`. It returns the sum of these parameters.

**Function f2**

`f2` is another simple function that takes an object `p` as its parameter. The object has properties corresponding to the 7 parameters in `f1`. `f2` returns the sum of the values of these properties.

Now, let's examine the options being compared:

* **Multiple Parameters**: This option passes each individual parameter (e.g., `data.a`, `data.b`) to `f1` separately.
* **Existing Parameter Object**: In this approach, the existing object `data` is passed to `f2` as-is.
* **Parameter Object with Spreading**: Here, the object `data` is spread using the syntax `{ ...data, g: Math.random() }`, and then passed to `f2`. This creates a new object that inherits from `data` and adds the key-value pair `g: Math.random()`.
* **New Parameter Object**: In this case, a completely new object is created by passing `{ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() }` to `f2`.

**Pros and Cons of each approach**

* **Multiple Parameters**: This approach can lead to better performance since the function is called with a smaller number of arguments. However, it may require more overhead for parameter validation.
* **Existing Parameter Object**: Passing the existing object as-is can be convenient, but it might not always be available or consistent across different instances of the object.
* **Parameter Object with Spreading**: This approach creates a new object that inherits from `data` and adds the key-value pair `g: Math.random()`. It can lead to performance issues if the spreading process is costly. On the other hand, it ensures that the passed object has all the required properties.
* **New Parameter Object**: Creating a new object for each call can be inefficient in terms of memory allocation and garbage collection.

**Library usage**

The `Math.random()` function is used in various test cases to generate random values. This is likely intended to simulate dynamic or unpredictable behavior in real-world scenarios.

**Special JS features or syntax**

There are no notable special features or syntax used in this benchmark. The focus is on comparing different approaches to passing arguments to functions.

**Other alternatives**

If the goal is to measure performance, some alternative approaches could be explored:

* Using a library like `lodash` to provide a consistent way of passing objects with spread syntax
* Implementing the tests using a JavaScript testing framework like Jest or Mocha
* Utilizing WebAssembly or other low-level optimization techniques for better performance

Keep in mind that these alternatives might not directly address the specific question being asked, but they can be useful tools in general for measuring and optimizing JavaScript performance.

Latest run results:

Run details: (Test run date: 14 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Multiple parameters	4590313.0 Ops/sec
Existing parameter object	8174136.5 Ops/sec
Parameter object with spreading	9163743.0 Ops/sec
New parameter object	13282432.0 Ops/sec

Related benchmarks:

JS multiple parameters vs parameter object 2 (version: 0)

Comparing performance of: Multiple parameters vs Existing parameter object vs Parameter object with spreading vs New parameter object

Created: 4 years ago by: Guest

Jump to the latest result

Multiple parameters

Existing parameter object

Parameter object with spreading

New parameter object

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):