Benchmark: path regex bis 2

Script Preparation code:

var precomp = /[^A-Za-z0-9.-]+|(?=[-A-Za-z])|(?<=[A-Za-z])|(?<=\.\d+)(?=\.)/g;
var test = "M 0 0 L 10 10 L10 10 L20 20 M 0 0 L 10 10 L10 10 L20 20 M 0 0 L 10 10 L10 10 L20 20 M 0 0 L 10 10 L10 10 L20 20";

Tests:

precompiled
test.split(precomp);
literal
test.split(/[^A-Za-z0-9.-]+|(?=[-A-Za-z])|(?<=[A-Za-z])|(?<=\.\d+)(?=\.)/g);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
precompiled
literal

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

I'll explain the benchmark in detail.

**Benchmark Definition**

The benchmark definition is a JSON object that describes the test case. In this case, there are two benchmark definitions:

1. `test.split(precomp);`
2. `test.split(/[^A-Za-z0-9.-]+|(?=[-A-Za-z])|(?<=[A-Za-z])|(?<=\\.\\d+)(?=\\.)/g);`

Both benchmarks test the performance of the `split()` method in JavaScript.

**Options Compared**

The two benchmark definitions compare different approaches to regular expression splitting:

1. **Precompiled Regular Expression**: The first benchmark definition, `"test.split(precomp);"`, uses a precompiled regular expression (`precomp`) that is stored in a variable before running the test. This approach is likely optimized for performance since the regular expression engine can reuse the compiled pattern multiple times.
2. **Literal Regular Expression**: The second benchmark definition, `"test.split(/[^A-Za-z0-9.-]+|(?=[-A-Za-z])|(?<=[A-Za-z])|(?<=\\.\\d+)(?=\\.)/g);"`, uses a literal regular expression string that is passed directly to the `split()` method. This approach may incur additional overhead due to the need to parse and compile the regular expression string.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **Precompiled Regular Expression**: Pros:
	+ May be faster since the regular expression engine can reuse the compiled pattern.
	+ Can reduce the number of times the regular expression engine needs to parse and compile the pattern.
*   Cons:
	+ Requires storing the precompiled regular expression in a variable, which may add memory overhead.
	+ May not work correctly if the regular expression is modified or updated dynamically.

Literal Regular Expression:

Pros:

*   Easy to implement and understand.
*   Can be easily modified or updated dynamically.

Cons:

*   May incur additional overhead due to parsing and compiling the regular expression string.
*   May not be as performant as precompiling the regular expression.

**Library**

There is no explicit library mentioned in the benchmark definition. However, it's likely that the `split()` method uses a built-in JavaScript library or engine that provides regular expression functionality.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax used in this benchmark. The regular expressions used are standard and widely supported across modern browsers.

**Other Considerations**

When running this benchmark, it's essential to consider the following factors:

*   **Browser Support**: Regular expressions are a fundamental part of JavaScript, but different browsers may implement them slightly differently.
*   **JavaScript Engine**: The performance of the `split()` method can vary depending on the specific JavaScript engine being used (e.g., V8 in Chrome, SpiderMonkey in Firefox).
*   **System Resources**: Running this benchmark on a resource-constrained device or system might not produce accurate results due to various overheads.

**Alternatives**

Other alternatives for measuring performance might include:

*   **Native Benchmarking Tools**: Using native benchmarking tools like `node-benchmark` (for Node.js) or `BenchmarkJS` (for general JavaScript benchmarks).
*   **WebAssembly Benchmarks**: Creating a WebAssembly version of the benchmark to measure performance in a more controlled environment.
*   **Artificial Intelligence-Driven Benchmarking**: Using AI-driven techniques to generate customized benchmarks tailored to specific use cases and hardware configurations.

Keep in mind that these alternatives might have their own set of considerations, pros, and cons.

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.54 Safari/537.36

Browser/OS: Chrome 94 on Linux

View result in a separate tab

Test name	Executions per second
precompiled	198437.9 Ops/sec
literal	198574.8 Ops/sec

Related benchmarks:

path regex bis 2 (version: 0)

Comparing performance of: precompiled vs literal

Created: 3 years ago by: Guest

Jump to the latest result

precompiled

literal

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):