Benchmark: Lazy Quantifier and non capturing group vs Greedy Quantifier with capturing group REGEX B@B

Tests:

greedy capturing
new RegExp("^([^./]+\\.)*slack.com").test("sub1.sub2.slack.com/");
lazy non capturing
new RegExp("^(:?[^./]+\\.)*?slack.com").test("sub1.sub2.slack.com/");

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
greedy capturing
lazy non capturing

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
greedy capturing	7256858.5 Ops/sec
lazy non capturing	7673621.0 Ops/sec

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 definition and test cases to understand what is being tested.

**Benchmark Definition**

The benchmark definition consists of two parts:

1. **Regular Expression (REGEX) Syntax**: The script preparation code defines two REGEX patterns:
	* `new RegExp("^([^./]+\\.)*slack.com").test("sub1.sub2.slack.com/")`
	* `new RegExp("^(:?[^./]+\\.)*?slack.com").test("sub1.sub2.slack.com/")`

These REGEX patterns are designed to match URLs that end with `.slack.com`.

2. **Quantifier Usage**: The benchmark defines two types of quantifiers:
	* Greedy capturing: `^([^./]+\\\\\.)*slack.com`
	+ In this pattern, the `(.*?)` group matches any characters (including none) between the `.` and the domain name, using a greedy approach.
	* Lazy non-capturing: `^(:?[^./]+\\.)*slack.com`
	+ In this pattern, the `(?:)` group matches any characters (including none) between the `.` and the domain name, using a lazy approach.

**Options Compared**

The benchmark compares two different approaches to match the URL patterns:

1. **Greedy Capturing**: The first REGEX pattern uses greedy capturing (`^([^./]+\\\\\.)*slack.com`). This approach matches as much of the string as possible between the `.` and the domain name, but may lead to inefficient matching if the target string is shorter than expected.
2. **Lazy Non-Capturing**: The second REGEX pattern uses lazy non-capturing (`^(:?[^./]+\\.)*slack.com`). This approach matches the least amount of characters between the `.` and the domain name, which can lead to more efficient matching if the target string is shorter than expected.

**Pros and Cons**

Here are some pros and cons for each approach:

Greedy Capturing:
Pros: May match longer strings due to greedy behavior.
Cons: Can be inefficient when the target string is shorter than expected.

Lazy Non-Capturing:
Pros: More efficient when the target string is shorter than expected.
Cons: May not match longer strings due to lazy behavior.

**Library and Purpose**

None of the REGEX patterns use a specific library. The built-in `RegExp` object in JavaScript is used for both patterns.

**Special JS Feature or Syntax**

The benchmark uses a special syntax feature called "raw" URLs, which are represented by the `sub1.sub2.slack.com/` URL string. This is likely used to test the REGEX pattern's behavior on specific input data.

**Other Alternatives**

If you wanted to implement this benchmark in your own tooling, you could consider using a similar approach with different quantifier strategies or testing other types of REGEX patterns. Some alternatives include:

* Using a different REGEX engine, such as PCRE (Perl-Compatible Regular Expressions) or the JavaScript `RegExp` engine's alternatives.
* Testing the performance of different caching mechanisms for REGEX patterns.
* Adding more test cases to cover additional scenarios, such as edge cases or specific character sets.

Keep in mind that this benchmark is specifically designed for measuring the performance difference between two approaches using a particular REGEX pattern. If you were to modify it, you might need to adjust the approach and implementation accordingly.

Related benchmarks:

Lazy Quantifier and non capturing group vs Greedy Quantifier with capturing group REGEX B@B (version: 0)

Comparing performance of: greedy capturing vs lazy non capturing

Created: 2 years ago by: Guest

Jump to the latest result

greedy capturing

lazy non capturing

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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