Benchmark: Test "new RegExp(string)" vs "new RegExp(/regexp/)" vs "/regexp/"

Script Preparation code:

var string = "Hello world!";
var regexA = /Hello/;
var regexB = new RegExp("Hello", 'gi');
var regexC = new RegExp(/Hello/, 'gi');
var regexD = () => new RegExp(/Hello/, 'gi')

Tests:

regexA.test
regexA.test(string);
regexB.test
regexB.test(string);
regexC.test
regexC.test(string);
regexD.test
regexD().test(string);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
regexA.test
regexB.test
regexC.test
regexD.test

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

**What is being tested?**

The provided benchmark tests the performance of creating regular expressions in different ways, specifically:

1. `new RegExp(string)`: Creating a regular expression from a string literal.
2. `new RegExp(/regexp/)`: Creating a regular expression from a forward slash (`/`) followed by a regex pattern.
3. Function expression with a closure: `() => new RegExp(/Hello/, 'gi')`.

**Options compared**

The benchmark compares the performance of these three approaches:

1. **Literal syntax**: Using string literals to create regular expressions, as in `new RegExp("Hello", "gi")`.
2. **Forward slash syntax**: Using forward slashes (`/`) followed by a regex pattern, as in `new RegExp(/Hello/, 'gi')`.
3. **Function expression with closure**: Defining a function that returns a new regular expression using the arrow function syntax, as in `( () => new RegExp(/Hello/, 'gi'))`.

**Pros and cons of each approach**

1. **Literal syntax**:
	* Pros: Easy to read and write, as it uses familiar string literal syntax.
	* Cons: May be slower than the other two approaches due to potential parsing overhead.
2. **Forward slash syntax**:
	* Pros: Can be faster than the literal syntax approach, as it avoids parsing overhead.
	* Cons: Requires careful attention to regex pattern escaping and quoting.
3. **Function expression with closure**:
	* Pros: Offers a compact way to create regular expressions while avoiding explicit function creation.
	* Cons: May be less readable for some developers due to the use of an arrow function.

**Library usage**

In this benchmark, the `RegExp` object is used from the built-in JavaScript library. The purpose of `RegExp` is to provide support for regular expression matching and operations.

**Special JS feature or syntax**

The test uses a special syntax called "arrow functions" (`() => ...`) which was introduced in ECMAScript 2015 (ES6). Arrow functions are used to create small, concise functions that do not have their own `this` context. In this case, the arrow function is used as a closure to encapsulate the regular expression creation.

**Other alternatives**

If these three approaches were not being compared, other alternatives for creating regular expressions might include:

* Using a dedicated regex library or module (e.g., UglifyJS's `require('uglifyjs/lib/regex')`)
* Using a different syntax, such as using the `RegExp` constructor with a string literal and then calling `RegExp` on it (`new RegExp("Hello", "gi").test(string)`)

However, in this specific benchmark, the focus is on comparing the performance of creating regular expressions using these three approaches.

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36

Browser/OS: Chrome 114 on Linux

View result in a separate tab

Test name	Executions per second
regexA.test	11711938.0 Ops/sec
regexB.test	12568357.0 Ops/sec
regexC.test	9527319.0 Ops/sec
regexD.test	2774373.0 Ops/sec

Related benchmarks:

Test "new RegExp(string)" vs "new RegExp(/regexp/)" vs "/regexp/" (version: 0)

Comparing performance of: regexA.test vs regexB.test vs regexC.test vs regexD.test

Created: one year ago by: Guest

Jump to the latest result

regexA.test

regexB.test

regexC.test

regexD.test

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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