Benchmark: function vs arrow function

Tests:

function
var curry = function(fn) { var prevArgs = Array.prototype.slice.call(arguments, 1); return fn.length <= prevArgs.length ? fn(...prevArgs) : function() { var nextArgs = Array.prototype.slice.call(arguments); return curry(fn, ...prevArgs, ...nextArgs); }; }; function volume(l, w, h) { return l * w * h; } var curring = curry(volume); curring(1)(2)(3); curring(1, 2, 3); curring(1, 3)(2); curring(1)()(2)(3);
arrow
var curry = (fn, ...args) => fn.length <= args.length ? fn(...args) : (...more) => curry(fn, ...args, ...more); function volume(l, w, h) { return l * w * h; } var curring = curry(volume); curring(1)(2)(3); curring(1, 2, 3); curring(1, 3)(2); curring(1)()(2)(3);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
function
arrow

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**Benchmark Definition**

The benchmark is designed to compare two approaches: using traditional functions and arrow functions (also known as closures) in JavaScript.

**What are we testing?**

We're testing how the execution time of a function differs when it's implemented as an arrow function versus a traditional function. The focus is on the `curry` function, which is a higher-order function that takes another function as an argument and returns a new function with partially applied arguments.

**What are we comparing?**

We're comparing two approaches:

1. **Traditional Function**: Using the `var curry = function(fn) { ... }` syntax to define the `curry` function.
2. **Arrow Function**: Using the `var curry = (fn, ...args) => { ... }` syntax to define the `curry` function.

**Pros and Cons of each approach:**

1. **Traditional Function**:
	* Pros: More explicit code structure, easier to understand for some developers.
	* Cons: Can be less readable, more verbose, and may lead to more errors due to the need to manually manage scope and closures.
2. **Arrow Function**:
	* Pros: Concise syntax, reduces boilerplate code, and can improve readability.
	* Cons: May require more attention to scoping rules (e.g., using `let` or `const` instead of `var`) to avoid issues with function context.

**Library and Special JavaScript Features**

There are no libraries used in this benchmark. However, it's worth noting that the use of arrow functions requires a specific syntax and understanding of JavaScript's scope rules.

**Other Considerations**

The test cases cover various scenarios, including:

* Applying multiple arguments to the partially applied function (e.g., `currying(1)(2)(3)`).
* Passing different numbers of arguments to the partially applied function (e.g., `currying(1, 2, 3)`, `currying(1, 3)(2)`).

**Alternatives**

Other alternatives for implementing currying functions include:

* Using a library like Lodash or Ramda, which provide built-in curry functions.
* Implementing the curry function manually using recursion or loops.
* Using a functional programming approach with immutable data structures.

Keep in mind that these alternatives might have different performance characteristics and may not be as concise as arrow functions.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.0.0 Safari/537.36

Browser/OS: Chrome 104 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
function	124172.1 Ops/sec
arrow	694210.5 Ops/sec

Related benchmarks:

function vs arrow function (version: 0)

Comparing performance of: function vs arrow

Created: 2 years ago by: Registered User

Jump to the latest result

function

arrow

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):