Benchmark: Local or Global - MeasureThat.net

Tests:

Global
const isPalindrome = (str) => { const strLowerCase = str.toLowerCase(); return strLowerCase === [...strLowerCase].reverse().join(''); }; const palindromeChecker = (arr) => arr.map((word) => ({ word, isPalindrome: isPalindrome(word), })); console.log(palindromeChecker(['Racecar', 'Hello', 'Radar', 'Foo'])); console.log(palindromeChecker(['Bar', 'Civic', 'World', 'Earth']));
Local
const palindromeChecker = (arr) => { const isPalindrome = (str) => { const strLowerCase = str.toLowerCase(); return strLowerCase === [...strLowerCase].reverse().join(''); }; return arr.map((word) => ({ word, isPalindrome: isPalindrome(word), })); }; console.log(palindromeChecker(['Racecar', 'Hello', 'Radar', 'Foo'])); console.log(palindromeChecker(['Bar', 'Civic', 'World', 'Earth']));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Global
Local

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided JSON benchmark definition and test cases.

**Benchmark Definition**

The given JSON represents a JavaScript microbenchmarking framework, where users can define and run their own benchmarks. The provided benchmark has two variants:

1. **Local**: In this approach, the `isPalindrome` function is defined directly within the `palindromeChecker` function's scope.
2. **Global**: In this approach, the `isPalindrome` function is defined at the top level of the script, outside of any function or scope.

**Options Comparison**

The two approaches differ in how the `isPalindrome` function is accessed and executed.

* **Local (Function-Scoped)**:
	+ Pros:
		- Less overhead due to fewer function lookups.
		- Easier to manage variable scoping.
	+ Cons:
		- Can lead to increased memory usage due to more variables in scope.
		- May incur additional overhead for function calls and returns.
* **Global (Top-Level)**:
	+ Pros:
		- Typically less memory-intensive, as fewer variables are in scope.
		- Can be faster, as the `isPalindrome` function is closer to the execution point.
	+ Cons:
		- More overhead due to additional function lookups and potential variable captures.
		- Requires careful management of global namespace pollution.

**Considerations**

When choosing between these approaches, consider the following factors:

* **Performance**: For simple functions like `isPalindrome`, the difference in performance might be negligible. However, for more complex functions or those with heavy dynamic scope, the Global approach might incur unnecessary overhead.
* **Code Organization**: If your codebase is already well-organized and easy to follow, the Local approach might be a better fit. However, if you're working on a large project with many interconnected components, the Global approach can provide more centralized control over global variables.
* **Memory Usage**: For benchmarking purposes, memory usage is often a concern. The Global approach tends to be more memory-efficient due to reduced scope and variable lifetime.

**Library: Lodash (Not Used)**

The provided JSON benchmark definition doesn't explicitly mention using the Lodash library. However, if we were to analyze the `palindromeChecker` function, it resembles a common use case for Lodash's `map()` function, which could be applied to the array of words. While not shown in this specific example, it highlights how libraries like Lodash can simplify code and improve performance.

**Special JS Feature/Syntax (None)**

There are no special JavaScript features or syntax used in these benchmark definitions. The examples focus on demonstrating the difference between two programming approaches rather than showcasing cutting-edge language features.

**Alternative Approaches**

If you're considering alternative approaches for your benchmarks, consider the following:

* **Just-In-Time (JIT) Compilation**: Some engines like SpiderMonkey (Firefox) and V8 (Chrome) offer JIT compilation, which can improve performance at runtime. This approach can be beneficial for more complex functions or those with a large number of iterations.
* **Ahead-Of-Time (AOT) Compilation**: AOT compilation involves compiling code to machine code beforehand. This approach can reduce the overhead associated with dynamic compilation and execution.

For most use cases, the Local vs Global approach should suffice, but understanding these alternative strategies can provide deeper insights into performance optimization and JavaScript engine internals.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:83.0) Gecko/20100101 Firefox/83.0

Browser/OS: Firefox 83 on Windows

View result in a separate tab

Test name	Executions per second
Global	16743.8 Ops/sec
Local	16969.4 Ops/sec

Related benchmarks:

Local or Global (version: 0)

Comparing performance of: Global vs Local

Created: 3 years ago by: Guest

Jump to the latest result

Global

Local

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):