Benchmark: mybencmark11111 - MeasureThat.net

Script Preparation code:

var if1 = true;
var if2 = true;
var if3 = false;

function a() {
  var b = {};
  
  if (if1) {
    b.a = document.createElement("a");
  }
  if (if2) {
    b.b = document.createElement("a");
  }
  if (if3) {
    b.c = document.createElement("a");
  }
  return b;
}

function c() {
  var d = [];
  
  if (if1) {
    d.push(document.createElement("a"));
  }
  if (if2) {
    d.push(document.createElement("a"));
  }
  if (if3) {
    d.push(document.createElement("a"));
  }
  return d;
}

Tests:

test1
for (let i = 0; i < 1000; ++i) { a(); }
test2
for (let i = 0; i < 1000; ++i) { c(); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
test1
test2

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark, which is a small program designed to measure the performance of specific parts of code. The benchmark definition includes:

1. **Script Preparation Code**: This code is executed only once before running the actual benchmarking tests. It sets up variables `if1`, `if2`, and `if3` with boolean values.
2. **Function a()**: This function creates DOM elements ( `<a>` tags) in an object (`b`) based on the value of `if1`, `if2`, and `if3`. The number of created elements depends on the value of these conditions.

The script is designed to test the performance of creating DOM elements.

**Function c()**

This function creates a JavaScript array (`d`) by pushing DOM elements ( `<a>` tags) into it, also based on the values of `if1`, `if2`, and `if3`. The number of created elements depends on the value of these conditions.

The purpose of this function is to test the performance of creating arrays with DOM elements.

**Test Cases**

There are two test cases defined:

1. **test1**: This test case runs the function `a()` in a loop 1000 times.
2. **test2**: This test case runs the function `c()` in a loop 1000 times.

Both tests aim to measure the performance of creating DOM elements and arrays, respectively.

**Options Compared**

The benchmark compares two approaches:

1. Creating DOM elements in an object (`b`) using the `if` statement (Function `a()`)
2. Creating DOM elements in an array (`d`) using the `if` statement (Function `c()`)

**Pros and Cons**

**Creating DOM elements in an object (`b`):**

Pros:

* Can be more efficient when working with complex data structures
* May be faster for large datasets

Cons:

* Requires creating multiple objects, which can lead to memory allocation overhead
* May not be suitable for situations where a single array or container is needed

**Creating DOM elements in an array (`d`):**

Pros:

* More memory-efficient than creating multiple objects
* Suitable for situations where a single array or container is needed

Cons:

* Can lead to slower performance when working with large datasets, as the browser needs to allocate and manage more memory

**Other Considerations**

* The benchmark does not account for other factors that can affect performance, such as:
	+ Cache effects
	+ Browser-specific optimizations
	+ Hardware differences

**Library Used**

The `document.createElement()` function is a part of the DOM API, which allows creating new HTML elements.

**Special JS Feature/ Syntax**

There are no specific JavaScript features or syntax used in this benchmark. The code uses standard JavaScript constructs, such as functions, variables, and conditional statements.

**Alternatives**

Other alternatives for measuring performance or optimizing code might include:

* Using WebAssembly (WASM) to compile code for performance-critical sections
* Utilizing browser-specific APIs or optimizations, such as `requestIdleCallback()` or `Web Workers`
* Employing parallel processing techniques using modern JavaScript libraries like `worker_threads` or `p-queue`

Keep in mind that the best approach will depend on the specific use case and requirements of your project.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36

Browser/OS: Chrome 114 on Windows

View result in a separate tab

Test name	Executions per second
test1	583.8 Ops/sec
test2	577.8 Ops/sec

Related benchmarks:

mybencmark11111 (version: 0)

Comparing performance of: test1 vs test2

Created: one year ago by: Guest

Jump to the latest result

test1

test2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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