Benchmark: iframe vs window (new)

Script Preparation code:

var iframe = document.createElement("iframe");
iframe.src = "about:blank";
document.documentElement.appendChild(iframe);
var _window = iframe.contentWindow;

Tests:

Iframe string
for(var i = 0; i < 200000; i++) { new _window.String("a random string").split(""); }
window string
for(var i = 0; i < 200000; i++) { new String("a random string").split(""); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Iframe string
window string

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.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmark test on the MeasureThat.net website. The benchmark compares the performance of two approaches: using an iframe to access the global window object (`_window`) versus accessing it directly through the `window` property.

**What is being tested?**

In this benchmark, the focus is on the string manipulation method used in JavaScript, specifically the use of `String()` and `split()` methods. The test cases are designed to measure the performance of these methods when working with large strings.

**Options compared**

Two options are being compared:

1. **Using an iframe to access the global window object (`_window`)**: In this approach, a new iframe is created, its content window is accessed using `_window`, and then string manipulation operations are performed on that window.
2. **Accessing the global window object directly through `window`**: This approach involves directly accessing the global window object using the `window` property.

**Pros and Cons of each approach**

**Iframe Approach (`_window`)**

Pros:

* Can be useful in certain scenarios where the global window object is not available or needs to be isolated.
* May provide better performance due to reduced overhead from accessing the global scope.

Cons:

* Creates a new iframe, which can lead to increased memory usage and potential issues with browser compatibility.
* May introduce additional overhead due to the creation and manipulation of the iframe.

**Direct Access (`window`)**

Pros:

* Is generally faster and more straightforward than using an iframe.
* Does not create any additional overhead or memory usage.

Cons:

* May have performance limitations when dealing with very large strings, as it may require repeated lookups in the global scope.

**Library and Special JS Feature**

In this benchmark, no specific JavaScript library is used. However, the use of `String()` and `split()` methods is notable. These methods are built-in to JavaScript and do not rely on any external libraries.

**Special JS Feature**

The benchmark does not explicitly test or utilize any special JavaScript features such as ES6 classes, async/await, or modernized syntax. If any such features were used in the script preparation code, they would likely be ignored by MeasureThat.net's benchmarking process.

**Other Alternatives**

If you're interested in exploring alternative approaches for similar benchmarks, consider the following:

* Using a virtual DOM library like React or Preact to compare rendering performance.
* Implementing a custom parser for regular expressions to compare performance with built-in `RegExp` methods.
* Measuring the performance of different data structures, such as arrays vs. linked lists, in JavaScript.

Keep in mind that each benchmark should be tailored to its specific use case and goals, and exploring alternative approaches can help ensure a more comprehensive understanding of JavaScript performance and optimization techniques.

Related benchmarks:

iframe vs window (new) (version: 0)

Comparing performance of: Iframe string vs window string

Created: 5 years ago by: Guest

Jump to the latest result

Iframe string

window string

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):