Benchmark: function versus const arrow function

Tests:

const
const globalRand = Math.random(); const rand = (n1) => { const scope1 = Math.random()*n1; const inner = (n2) => { const scope2 = n1*Math.random(); return (n3) => ({[`${n1*n2*n3}`]: scope2*n3}); } return inner(scope1); } const fn = rand(Math.random()); fn();
function
const globalRand = Math.random(); function rand(n1) { const scope1 = Math.random()*n1; function inner(n2) { const scope2 = n1*Math.random(); return function(n3) { return {[`${n1*n2*n3}`]: scope2*n3} } } return inner(scope1); } const fn = rand(Math.random()); fn();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
const
function

Fastest: N/A

Slowest: N/A

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

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**Benchmark Overview**

The provided benchmark is designed to compare the performance of two approaches: using `const` and using `function` in JavaScript. The benchmark tests the execution speed of an anonymous function with varying levels of complexity.

**Options Compared**

Two options are compared:

1. **Using `const`**: This approach uses a constant variable, `globalRand`, initialized with a random value. The function, `rand`, takes a single argument, `n1`, and returns another function, `inner`, which also takes an argument, `n2`. The returned function, in turn, takes an argument, `n3`, and returns an object with a property whose key is the product of `n1`, `n2`, and `n3`.
2. **Using `function`**: This approach uses a named function, `rand`, which takes a single argument, `n1`. The function returns another function, `inner`, which also takes an argument, `n2`. The returned function, in turn, takes an argument, `n3`, and returns an object with a property whose key is the product of `n1`, `n2`, and `n3`.

**Pros and Cons**

Here are some pros and cons of each approach:

**Using `const`**

Pros:

* The constant variable, `globalRand`, can be reused across multiple function calls.
* The function, `inner`, can take advantage of the fact that it's a closure (has access to its outer scope) and avoid reinitializing variables.

Cons:

* The use of a complex expression in the return statement may lead to slower execution times due to the overhead of evaluating the expression.

**Using `function`**

Pros:

* The function, `inner`, can be defined separately from the main function, making it easier to understand and maintain.
* The use of a named variable reduces the complexity of the expression in the return statement.

Cons:

* Reinitializing variables with each function call may lead to slower execution times due to the overhead of creating new variables.

**Library Used**

None. This benchmark only uses built-in JavaScript features.

**Special JS Feature/Syntax**

The benchmark uses a feature called "arrow functions" (introduced in ECMAScript 2015) for both `const` and `function` approaches. Arrow functions provide a concise way to define small, anonymous functions without the overhead of creating a new scope.

**Considerations**

* The benchmark only measures the execution speed of the function calls, so it may not accurately represent the performance characteristics of these code snippets in real-world scenarios.
* The use of random values and nested function calls makes the benchmark results dependent on the specific inputs used during testing.

**Alternatives**

Some alternative approaches to benchmarking this code snippet include:

* Using a simpler input format, such as a fixed number for `n1` and `n2`.
* Using a more comprehensive benchmarking framework that accounts for factors like memory allocation, garbage collection, and thread scheduling.
* Running the benchmark on different platforms or browsers to evaluate its performance variability.

Keep in mind that these alternatives may require modifications to the benchmark code itself.

Related benchmarks:

function versus const arrow function (version: 0)

Comparing performance of: const vs function

Created: 2 years ago by: Guest

Jump to the latest result

const

function

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):