Benchmark: Invocation - MeasureThat.net

Script Preparation code:

function foobar() {}
var args = [1, '2', {3: 4}];

Tests:

Apply
foobar.apply(null, args);
Spread
foobar(...args);
Flat
foobar(args[0], args[1], args[2]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Apply
Spread
Flat

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 definition and test cases to understand what is being tested.

**Benchmark Definition**

The provided JSON defines a benchmark named "Invocation". The description states that this benchmark tests the performance of three different approaches: `apply`, `spread`, and `flat` when invoking a function with an array of arguments.

**Script Preparation Code**

The script preparation code defines a simple JavaScript function `foobar()` without any implementation, and then declares an array `args` containing three elements: `[1, '2', {3: 4}]`.

**Html Preparation Code**

There is no HTML preparation code provided, which means the benchmark only tests the JavaScript code.

**Individual Test Cases**

The benchmark consists of three individual test cases:

1. **Apply**: The benchmark definition uses the `apply()` method to invoke the `foobar()` function with `null` as the first argument and the `args` array as subsequent arguments.
2. **Spread**: This benchmark definition uses the spread operator (`...`) to pass the `args` array as individual arguments to the `foobar()` function.
3. **Flat**: The third benchmark definition passes each element of the `args` array as separate arguments to the `foobar()` function using a comma-separated syntax.

**Library**

There is no explicit library mentioned in the benchmark definition. However, the use of the spread operator (`...`) and the `apply()` method indicates that the benchmark uses built-in JavaScript features.

**Special JS Features/Syntax**

The spread operator (`...`) was introduced in ECMAScript 2015 (ES6). It allows for more concise function invocations by enabling the direct passing of arrays or objects as arguments.

Here are some pros and cons of each approach:

* **Apply()**: This method is older than `spread()` and provides a way to invoke a function with an array of arguments. However, it can lead to slower performance due to the overhead of creating an activation record.
	+ Pros: more portable across different JavaScript versions.
	+ Cons: less readable and maintainable compared to modern alternatives.
* **Spread**: This method is faster and more concise than `apply()`, as it eliminates the need for an activation record. However, it may not work in older JavaScript environments that don't support it.
	+ Pros: more readable and maintainable, faster performance.
	+ Cons: requires ES6+ compatibility, may not work on older browsers.
* **Flat**: This approach is less common and may not be supported by all JavaScript engines. It uses a comma-separated syntax to invoke the function with each element of the array as an argument.
	+ Pros: more readable than `apply()` or spread.
	+ Cons: less efficient, may not work on older browsers.

**Other Alternatives**

In addition to these three approaches, other methods for invoking functions with arrays of arguments include:

* Using a loop to iterate over the elements of the array and invoke the function individually.
* Using a library like `lodash` or `ramda`, which provide higher-order functions that can be used to work with arrays.

However, for this specific benchmark, only the three approaches mentioned above are being tested.

Related benchmarks:

Invocation (version: 0)

Function apply vs spread vs flat

Comparing performance of: Apply vs Spread vs Flat

Created: 5 years ago by: Guest

Jump to the latest result

Apply

Spread

Flat

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):