Benchmark: Typeof Window Check

Tests:

Memoize typeof call
let cachedGlobal; function getGlobal() { if (cachedGlobal) { return cachedGlobal; } if (typeof window !== 'undefined' && window) { cachedGlobal = window; } return cachedGlobal } for (let i = 0; i < 4000; i++) { const global = getGlobal(); }
Call typeof every time
function getGlobal() { if (typeof window !== 'undefined' && window) { return window; } } for (let i = 0; i < 4000; i++) { const global = getGlobal(); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Memoize typeof call
Call typeof every time

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 benchmark and explain what is being tested, compared, and their pros and cons.

**Benchmark Overview**

The test cases are designed to measure the performance difference between two approaches:

1. **Memoizing `typeof` check**: This approach caches the result of the `typeof window` check in a variable (`cachedGlobal`) and returns it on subsequent calls.
2. **Calling `typeof` every time**: This approach always checks if `window` is defined and returns its type.

**What's being tested?**

The benchmark tests the performance difference between these two approaches when calling `getGlobal()` (which returns the global object) 4000 times in a loop. The goal is to measure how much faster one approach is compared to the other.

**Library Used: None**

There are no external libraries used in this benchmark.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntax used in these test cases.

**Comparison Options and Pros/Cons:**

1. **Memoizing `typeof` check**
	* Cache the result of `typeof window` to avoid repeated checks.
	* Potential benefits:
		+ Improved performance by reducing the number of times `typeof window` is called.
		+ Can help reduce CPU usage.
	* Potential drawbacks:
		+ Adds extra memory allocation for the cached value.
		+ Might introduce cache invalidation issues if not managed properly.
2. **Calling `typeof` every time**
	* Always checks if `window` is defined, regardless of previous calls.
	* Potential benefits:
		+ Simplifies code and avoids potential caching issues.
	* Potential drawbacks:
		+ Slower performance due to repeated checks.

**Other Alternatives:**

If memoizing the `typeof` check doesn't seem like an optimal solution, alternative approaches could include:

1. **Using a more efficient type checking method**: Instead of using `typeof window`, consider using other methods that are faster and more accurate, such as `window === globalThis` (for modern browsers) or `window === window.top`.
2. **Optimizing the loop**: Consider optimizing the loop by reducing the number of iterations or using a more efficient data structure.
3. **Using a different caching mechanism**: Instead of memoizing the result of `typeof window`, consider using a different caching mechanism, such as a cache library or a custom implementation.

Keep in mind that these alternatives may not address the core issue (repeated checks) and might introduce additional complexity.

**Benchmark Results**

The provided benchmark results show that the "Memoize typeof call" test case outperforms the "Call typeof every time" test case. This suggests that memoizing the `typeof` check has a positive impact on performance, which is likely due to reduced repeated checks.

However, the actual performance difference may depend on various factors, such as the specific browser and version being tested, system resources, and other concurrent activities.

Related benchmarks:

Typeof Window Check (version: 0)

Memoizing a key typeof check in high frequency

Comparing performance of: Memoize typeof call vs Call typeof every time

Created: 4 years ago by: Registered User

Jump to the latest result

Memoize typeof call

Call typeof every time

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):