Benchmark: separate vs destructure

Script Preparation code:

window.test = props => { console.log(props); }

Tests:

separate
window.test({ a:1, b:2 });
destructure
window.test({...{ a:1, b:2 }});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
separate
destructure

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its test cases.

**Benchmark Definition**

The benchmark is defined as a JSON object with several properties:

* `Name`: A descriptive name for the benchmark, which in this case is "separate vs destructure".
* `Description`: An optional description of the benchmark, but it's empty in this case.
* `Script Preparation Code` and `Html Preparation Code`: These are code snippets that are executed before running the actual benchmark. The `Script Preparation Code` sets up a variable `window.test` as a function that takes an object as input, logs it to the console, and returns nothing (i.e., `console.log(props);`). The `Html Preparation Code` is empty in this case.

**Test Cases**

The benchmark consists of two test cases:

1. **"separate"`**: This test case runs the following code:
```javascript
window.test({ a: 1, b: 2 });
```
This means that the input object is passed as a separate argument to the `window.test` function.

2. **"destructure"`**: This test case runs the following code:
```javascript
window.test(({ a, b }) => ({ a, b }));
```
In this case, the input object is destructured using the arrow function syntax (`({ a, b }) => ...`) and its properties are passed as an object to the `window.test` function.

**What's being tested?**

The benchmark is testing how JavaScript engines handle object property access and passing objects between functions. Specifically:

* The "separate" test case checks if the engine passes the input object as a separate argument to the function.
* The "destructure" test case checks if the engine correctly deconstructs the input object using arrow function syntax.

**Options compared**

In this benchmark, two options are being compared:

1. **Separate argument**: Passing the input object as a separate argument to the function.
2. **Destructuring with arrow functions**: Using arrow functions to destructure the input object and pass its properties to the function.

**Pros and Cons of each approach**

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

* **Separate argument**:
	+ Pros: Easier to understand, more explicit syntax.
	+ Cons: May lead to slower performance due to additional overhead of passing separate arguments.
* **Destructuring with arrow functions**:
	+ Pros: More concise syntax, potentially faster performance due to reduced overhead.
	+ Cons: Less explicit syntax may make it harder for some developers to understand.

**Special JS feature or syntax**

The benchmark uses the following special JavaScript feature:

* Arrow function syntax (`=>`)

Arrow functions were introduced in ECMAScript 2015 (ES6) and provide a concise way to define small, single-expression functions. In this case, the `destructure` test case uses arrow functions to destructure the input object.

**Other alternatives**

If you want to create similar benchmarks or explore other aspects of JavaScript performance, here are some alternative ideas:

* Compare string concatenation vs template literals
* Test the performance of different array methods (e.g., `map`, `filter`, `forEach`)
* Benchmark the speed of different DOM manipulation techniques (e.g., using jQuery vs vanilla JS)
* Explore the performance of different data structures (e.g., arrays, objects, sets) in JavaScript

Related benchmarks:

separate vs destructure (version: 0)

Comparing performance of: separate vs destructure

Created: 5 years ago by: Guest

Jump to the latest result

separate

destructure

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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