Benchmark: Function typeof in High Frequency

Script Preparation code:

function test() {
  console.log('hi');
}

window.test = test;

Tests:

Call typeof every time
for (let i = 0; i < 5000; ++i) { if (typeof window.test === 'function') { const func = window.test; } }
Cache typeof
const seen = new Set(); for (let i = 0; i < 5000; ++i) { if (seen.has(window.test)) { const func = window.test; } else { if (typeof window.test === 'function') { seen.add(window.test); const func = window.test; } } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Call typeof every time
Cache typeof

Fastest: N/A

Slowest: N/A

Latest 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 JSON data and explain what's being tested in this JavaScript microbenchmark.

**Benchmark Overview**

The benchmark is designed to measure the performance of two approaches: calling `typeof` on a function every time, and caching the result of `typeof` for future calls.

**Script Preparation Code**

The script preparation code defines a simple function `test()` that logs "hi" to the console. This function will be used as the test subject throughout the benchmark.

```javascript
function test() {
  console.log('hi');
}
window.test = test;
```

This code sets up a global variable `window.test` that points to the `test()` function, making it accessible throughout the benchmark.

**Html Preparation Code**

Since there is no HTML preparation code provided, we can assume that this benchmark is running in a headless environment or using a simple web framework like Electron or Node.js.

**Test Cases**

There are two test cases:

1. **Call `typeof` every time**: This test case iterates over 5000 loops and checks if the global `window.test` variable has changed type (`typeof` will return `"function"`).
2. **Cache `typeof`**: In this test case, a `Set` named `seen` is created to keep track of the `window.test` variables. The loop iterates over 5000 times and checks if `window.test` is already in the `seen` set. If not, it adds it to the set and caches its type using `typeof`.

**What's Being Tested**

The benchmark measures the performance difference between these two approaches:

* **Approach 1: Call `typeof` every time**
	+ This approach involves checking if the global variable has changed type on each iteration.
	+ Pros:
		- Simple implementation
		- No need to store or compare values
	+ Cons:
		- Inefficient due to repeated `typeof` checks
		- May lead to increased CPU usage
* **Approach 2: Cache `typeof`**
	+ This approach involves storing and comparing values using a `Set`.
	+ Pros:
		- Can reduce the number of `typeof` calls
		- Can improve performance by avoiding unnecessary checks
	+ Cons:
		- Requires additional memory to store the `Set`
		- May lead to slower startup times

**Library: Set**

The `Set` data structure is a built-in JavaScript library that allows you to store unique values and check for membership. In this benchmark, the `Set` is used to cache the type of `window.test`.

**Special JS Feature/ Syntax**

There are no special JS features or syntax being tested in this benchmark.

**Other Alternatives**

Some alternative approaches to caching `typeof` could include:

* Using a `WeakMap` instead of a regular `Map` to store cached values.
* Implementing a more complex caching mechanism using JavaScript's built-in functions, such as `Object.create()` and `Object.assign()`.
* Using a third-party library like LRU Cache or memoization libraries.

Keep in mind that these alternatives may have different trade-offs in terms of performance, memory usage, and complexity.

Related benchmarks:

Function typeof in High Frequency (version: 0)

Caching function typeof

Comparing performance of: Call typeof every time vs Cache typeof

Created: 4 years ago by: Guest

Jump to the latest result

Call typeof every time

Cache typeof

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):