Benchmark: Measuring impact of closures

Script Preparation code:

let [a,b] = Math.random() < 0.5 ? [5,9] : [9,5];

let sum = 0;

function hello(x) { sum += x };

function f1(x) { hello(x + a) };
function f2(x) { f2.hello(x + b) }; Object.defineProperty(f2, "hello", { value: hello });

function f3(x) { hello(x + b) };
function f4(x) { f4.hello(x + a) }; Object.defineProperty(f4, "hello", { value: hello });

function f5(x) { f5.hello(x + f5.n) }; Object.defineProperty(f5, "hello", { value: hello }); Object.defineProperty(f5, "n", { value: a });
function f6(x) { f6.hello(x + f6.n) }; Object.defineProperty(f6, "hello", { value: hello }); Object.defineProperty(f6, "n", { value: b });

Tests:

f1
f1(i);
f2
f2(i);
f3
f3(i);
f4
f4(i);
f5
f5(i);
f6
f6(i);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
f1
f2
f3
f4
f5
f6

Fastest: N/A

Slowest: N/A

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/115.0.0.0 Safari/537.36

Browser/OS: Chrome 115 on Windows

View result in a separate tab

Test name	Executions per second
f1	3645259.5 Ops/sec
f2	3590228.8 Ops/sec
f3	3624467.8 Ops/sec
f4	3627131.8 Ops/sec
f5	2373211.0 Ops/sec
f6	2305061.5 Ops/sec

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

LLMs can make mistakes. Check important info.

The provided benchmark measures the performance impact of closures in JavaScript. Closures are functions that have access to their own scope and can "remember" variables from that scope even when the function is called outside of it.

In this specific benchmark, six test cases are defined:

1. `f1(x)`: Calls the `hello` function with an argument `x + a`.
2. `f2(x)`: Calls the modified `hello` function on an object `f2` with an argument `x + b`. The `hello` function is initially defined as `sum += x`, but it's later reassigned to also modify another variable.
3. `f3(x)`: Calls the same `hello` function as in `f1`, but uses a different variable `b`.
4. `f4(x)`: Similar to `f2`, but with `a` and `b` swapped between the object and the function call.
5. `f5(x)`: Calls the modified `hello` function on an object `f5` with an argument `x + f5.n`. The `n` property is initialized in the function definition.
6. `f6(x)`: Similar to `f1`, but uses the `n` property from the `f5` object.

Now, let's explore the options compared and their pros/cons:

**Option 1: Direct function call (`f1(x)`)**

* Pros: Simple and straightforward.
* Cons: The variable `a` is only accessible within the scope of the `hello` function, which might lead to unexpected behavior if the scope changes.

**Option 2: Object-based function call (`f2(x)`)**

* Pros: Allows the `hello` function to modify another variable (`b`) in addition to its original purpose. This can make it easier to test more complex scenarios.
* Cons: The object `f2` needs to be created and managed, which adds overhead.

**Option 3: Variable swap (`f4(x)`)**

* Pros: Swaps the roles of variables `a` and `b`, making it useful for testing cases where their order is crucial.
* Cons: Requires careful consideration of the variable dependencies.

**Option 4: Self-referential function call (`f5(x)`)**

* Pros: Allows the `n` property to be accessed within its own scope, which can simplify some tests.
* Cons: Can lead to unexpected behavior if the object's properties are modified unexpectedly.

**Option 5: Self-referential function call with a parameter (`f6(x)`)**

* Pros: Similar to `f5`, but uses an argument instead of an object property. This makes it easier to test different input values.
* Cons: Still relies on self-reference, which can be tricky to reason about.

Other alternatives could include:

* Using a different data structure, such as an array or a set, instead of objects and functions.
* Incorporating more complex logic or side effects into the benchmark to simulate real-world scenarios.
* Using a different JavaScript engine or version to test compatibility with various implementations.
* Adding additional test cases or variations to cover more edge cases.

Keep in mind that these alternatives will add complexity and potential variations, making it harder to understand the benchmark's intent.

Related benchmarks:

Measuring impact of closures (version: 7)

Comparing performance of: f1 vs f2 vs f3 vs f4 vs f5 vs f6

Created: one year ago by: Registered User

Jump to the latest result

f1

f2

f3

f4

f5

f6

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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