Benchmark: Test parameter object 4

Script Preparation code:

var number1 = 1;
var number2 = 2;

function f1 (a, b, c) { return a + b + c; }
function f2 ({a, b, c}) { return a + b + c;}

Tests:

Without parameter object
f1(number1, number2, Math.random());
with paramenter object
f2({a: number1, b: number2, c: Math.random()})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Without parameter object
with paramenter object

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Linux

View result in a separate tab

Test name	Executions per second
Without parameter object	5693032.0 Ops/sec
with paramenter object	5693307.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON data to understand what is being tested in this JavaScript microbenchmark.

**Benchmark Definition**

The benchmark definition is represented by a JSON object that contains two scripts: `f1` and `f2`. Both functions are designed to add three numbers together. The difference between them lies in how they handle function arguments:

*   **Script Preparation Code**: This section defines the variables `number1`, `number2`, and `Math.random()`, which will be used as input values for the functions.
*   **Html Preparation Code**: Since there is no HTML preparation code, this suggests that the benchmark might focus solely on the JavaScript execution aspect.

**Function Differences**

The two main differences between `f1` and `f2` are:

*   **Parameter Passing Style**: `f1` uses positional arguments (`a`, `b`, `c`), whereas `f2` uses an object literal syntax (`{a: number1, b: number2, c: Math.random()}`).
*   **Function Signature**: The function signatures for both `f1` and `f2` are identical, with the same parameters (`a`, `b`, `c`). However, `f2` uses a spread syntax (`{...}`, which is used to merge objects in JavaScript.

**Pros and Cons of Different Approaches**

*   **Positional Argument Style (f1)**:
    *   Pros: Efficient for simple functions with fixed parameters.
    *   Cons: Less readable when dealing with complex arguments or optional parameters.
*   **Object Literal Syntax (f2)**:
    *   Pros: More concise and easier to read, especially for complex objects with multiple properties.
    *   Cons: May be slower due to the overhead of object creation.

**Library Usage**

There is no explicit library usage in this benchmark. However, it's essential to note that some JavaScript engines may have built-in optimizations or features that affect execution performance, such as:

*   **Just-In-Time (JIT) compilation**: Some browsers like Chrome employ JIT compilation for performance optimization.
*   **Function caching**: Browsers might cache frequently called functions to improve performance.

**Special JS Features**

The benchmark uses the `Math.random()` function to introduce some randomness in the input values. This can help simulate real-world usage scenarios and ensure that the results are not skewed towards specific inputs.

**Alternatives**

Some alternatives for creating benchmarks include:

*   **Benchmarking frameworks**: Tools like Benchmark.js, Fastbench, or Micro-Benchmark provide a structured approach to benchmarking JavaScript code.
*   **WebAssembly (WASM) benchmarks**: If you're interested in WebAssembly, you can create benchmarks using the WASM runtime and explore its performance characteristics.

Keep in mind that each alternative has its own strengths and weaknesses.

Related benchmarks:

Test parameter object 4 (version: 0)

Comparing performance of: Without parameter object vs with paramenter object

Created: one year ago by: Guest

Jump to the latest result

Without parameter object

with paramenter object

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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