Benchmark: testasdfasdfasdf

Script Preparation code:

 var range = 10;
  
 function obj1()  {
  return {
    data: 1,
    a: 0,
    b: 0,
    c: 0,
    fx: function() {
      this.a += this.data;
      this.b += this.data;
      this.c += this.data;
    },
  };
}

function obj2()  {
  return {
    data: 1,
    a: 0,
    b: 0,
    c: 0,
  };
}

function fx(obj) {
  obj.a += obj.data;
  obj.b += obj.data;
  obj.c += obj.data;
}

var arr1 = [];
var arr2 = [];

for (let i = 0; i < range; i++) {
    arr1.push(obj1());    
}
for (let i = 0; i < range; i++) {
    arr2.push(obj2());    
}

Tests:

1
for (let i = 0; i < range; i++) { arr1[i].fx(); }
2
for (let i = 0; i < range; i++) { fx(arr2[i]); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2

Fastest: N/A

Slowest: N/A

Latest 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 JSON and explain what is being tested, compared, and the pros and cons of different approaches.

**Benchmark Definition**

The benchmark definition represents the code that will be executed to measure the performance of the JavaScript engine. In this case, there are two test cases:

1. `for (let i = 0; i < range; i++) {\r\n    arr1[i].fx();\r\n}`: This test case measures the execution time of calling the `fx` function on an object that is part of a large array (`arr1`). The `fx` function increments three properties (`a`, `b`, and `c`) of the object by its own value.

2. `for (let i = 0; i < range; i++) {\r\n    fx(arr2[i]);\r\n}`: This test case measures the execution time of calling a standalone `fx` function on an array of objects (`arr2`). The `fx` function also increments three properties (`a`, `b`, and `c`) of each object by its own value.

**Comparison**

The benchmark definition compares two approaches:

1. **Object-oriented approach**: In this test case, the `fx` function is called on an object that is part of a large array (`arr1`). This allows the compiler to optimize the calls to `fx` because it knows that there are multiple instances of the same function being called.
2. **Standalone function call**: In the second test case, the `fx` function is called directly on each element of an array (`arr2`) without any optimization.

**Pros and Cons**

1. **Object-oriented approach**:
	* Pros: Compiler can optimize calls to `fx` because it knows there are multiple instances.
	* Cons: May not accurately represent performance of standalone function calls.
2. **Standalone function call**:
	* Pros: Can provide a more accurate representation of the performance of standalone function calls.
	* Cons: Compiler may not be able to optimize these calls as effectively.

Other considerations:

* The use of `for` loops and arrays in both test cases ensures that the benchmark is focused on the execution time of calling functions, rather than other factors like memory allocation or object creation.
* The large value of `range` (10) increases the likelihood that any differences between the two approaches will be measurable.

**Libraries**

None of the provided code uses any external libraries. However, it's worth noting that modern JavaScript engines often rely on internal libraries and frameworks to optimize performance.

**Special JS Features or Syntax**

This benchmark does not use any special JavaScript features or syntax beyond what is typical in modern JavaScript programming.

Related benchmarks:

testasdfasdfasdf (version: 0)

sadfsadfasdf

Comparing performance of: 1 vs 2

Created: 3 years ago by: Guest

Jump to the latest result

1

2

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):