Benchmark: JS multiple parameters vs parameter object

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(); f1(data)
Parameter object with spreading
f1({ ...data, g: Math.random() })
New parameter object
f1({ 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 break down the provided JSON and explain what's being tested.

**Benchmark Definition**

The benchmark defines two functions, `f1` and `f2`, which take different numbers of arguments. The script preparation code shows the implementation of these functions:

```javascript
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;
}
```

The `f1` function takes seven arguments, while the `f2` function takes a single object with properties `a`, `b`, ..., `g`.

**Test Cases**

There are four test cases defined in the JSON:

1. **Multiple parameters**: This test case calls `f1` with all seven arguments directly.
```javascript
Benchmark Definition: f1(data.a, data.b, data.c, data.d, data.e, data.f, Math.random())
```
2. **Existing parameter object**: This test case sets a new value for the `g` property of the original object and then passes it to `f1`.
```javascript
Benchmark Definition: data.g = Math.random(); f1(data)
```
3. **Parameter object with spreading**: This test case uses the spread operator (`...`) to create a new object that includes all the properties of the original object, plus a new `g` property set to a random value.
```javascript
Benchmark Definition: f1({ ...data, g: Math.random() })
```
4. **New parameter object**: This test case creates a new object with all the same properties as the original object and adds a new `g` property set to a random value.
```javascript
Benchmark Definition: f1({ a: 1, b: 2, c: 3, d: 4, e: 5, f: 6, g: Math.random() })
```
**Library**

There is no explicit library mentioned in the JSON. However, it's worth noting that the use of `Math.random()` suggests that this benchmark might be related to performance comparisons between different JavaScript engines or implementations.

**Special JS Features/Syntax**

The use of the spread operator (`...`) in test case 3 is a relatively recent feature introduced in ECMAScript 2018 (ES2018). This syntax allows for creating new objects by copying the properties of an existing object and adding new ones. The `f2` function also uses this syntax to create a new object with some properties set.

**Pros and Cons**

Here are some pros and cons associated with each approach:

1. **Multiple parameters**: Passing all arguments directly might be the most straightforward approach, but it may not take advantage of any optimizations or caching mechanisms in the JavaScript engine.
2. **Existing parameter object**: This approach sets a new value for an existing property, which might trigger additional checks or optimization paths in the engine.
3. **Parameter object with spreading**: Using the spread operator creates a new object that includes all properties from the original object, plus a new one. This approach may be more efficient if the engine can optimize the creation of new objects or caching.
4. **New parameter object**: Creating a new object with all the same properties as the original and adding a new one might trigger additional checks or optimization paths in the engine.

**Other Alternatives**

If you want to explore alternative approaches, here are some ideas:

* Use an array instead of an object: For example, `f1([data.a, data.b, data.c, data.d, data.e, data.f, Math.random()])`
* Use a struct or record-like approach: Define a struct or record class that includes all the properties and use it to create objects.
* Experiment with different parameter layouts: Try passing parameters in different orders or arrangements to see how the engine optimizes.

Keep in mind that these alternatives might not directly relate to the performance characteristics you're trying to measure, but they can provide interesting insights into how the JavaScript engine handles different types of data and computations.

Latest run results:

Run details: (Test run date: 11 days ago)

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 130 on Android

View result in a separate tab

Test name	Executions per second
Multiple parameters	1777946.0 Ops/sec
Existing parameter object	2140742.8 Ops/sec
Parameter object with spreading	2262758.5 Ops/sec
New parameter object	2887353.0 Ops/sec

Related benchmarks:

JS multiple parameters vs parameter object (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):