Benchmark: RegExp constructor vs literal, constructing in function

Script Preparation code:

function getReConstructor() {
  return new RegExp('^[0-9a-fA-F]{24}$');
}
function getReLiteral() {
  return /^[0-9a-fA-F]{24}$/;
}

Tests:

new RegExp()
getReConstructor().test('132abc67219f019afe12901a')
Literal
getReLiteral().test('132abc67219f019afe12901a')

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
new RegExp()
Literal

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's dive into the world of JavaScript microbenchmarks and understand what's being tested on this provided JSON.

**Benchmark Purpose**

The primary goal of this benchmark is to compare the performance of two approaches:

1. Creating a new RegExp object using the `new RegExp()` constructor.
2. Using a literal regular expression string as a regex pattern.

This benchmark aims to measure which approach is faster, more efficient, and optimal for common use cases.

**Options Compared**

The two options being compared are:

1. **Literal Regular Expression**: This method uses a predefined regex pattern as a string literal. The benefits include:
	* Simplicity: No need to create a new RegExp object.
	* Reusability: Same pattern can be reused across multiple tests.
	* Clarity: Code is easier to read and understand.
However, this approach might have some drawbacks:
	* Limited flexibility: Regex patterns cannot be easily modified or extended.
	* Potential performance overhead due to string interpolation or concatenation.
2. **RegExp Constructor**: This method creates a new RegExp object using the `new RegExp()` constructor. The benefits include:
	* Flexibility: Regex patterns can be easily modified, extended, or reused across multiple tests.
	* Performance: Can lead to better performance due to optimized regex compilation.
However, this approach also has some drawbacks:
	* Complexity: Requires creating a new RegExp object, which might add overhead.

**Pros and Cons**

Both approaches have their advantages and disadvantages. The choice between them depends on the specific use case and requirements.

For most cases, using a literal regular expression string is sufficient and efficient. However, if you need more flexibility or performance, using the RegExp constructor might be a better option.

**Library Use**

There is no explicit library mentioned in this benchmark. However, it's worth noting that the `RegExp` object relies on JavaScript's built-in regex engine, which provides various features and optimizations for working with regular expressions.

**Special JS Feature/Syntax**

This benchmark does not explicitly use any special JavaScript features or syntax. The code is straightforward and focuses on testing two different approaches to creating regular expressions.

**Alternatives**

Other alternatives to compare the performance of RegExp constructors and literal regex patterns include:

1. **RegExp Literal Syntax**: Some browsers and JavaScript engines support a more concise syntax for literals, such as `^[0-9a-fA-F]{24}$` instead of `new RegExp('^[0-9a-fA-F]{24}$')`.
2. **Function-Based Regex**: Using function-based regex patterns, like `(function() { return '^[0-9a-fA-F]{24}$'; }())`, can also be compared to the existing approaches.
3. **Regexp Engine Optimizations**: Some browsers and engines provide optimizations for certain types of regex patterns or use cases, such as `String.prototype.test()` with a cached RegExp object.

These alternatives might offer different performance profiles or trade-offs in terms of complexity, flexibility, and readability, which could be explored in future benchmarks.

Related benchmarks:

RegExp constructor vs literal, constructing in function (version: 0)

Testing performance when using a new RegExp object vs a literal regex

Comparing performance of: new RegExp() vs Literal

Created: 6 years ago by: Guest

Jump to the latest result

new RegExp()

Literal

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):