Benchmark: trim + length VS regex with prepared rx

Script Preparation code:

var str = "  abc";
var rx = /\S{3,}/;

Tests:

trim + length
str.trim().length > 2
regex test
rx.test(str)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
trim + length
regex test

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and its various components.

**Benchmark Overview**

The provided benchmark is designed to compare two approaches for determining whether an input string contains at least 3 non-whitespace characters in sequence: using the `trim()` method followed by checking the length of the resulting string, and using a regular expression (regex) with a prepared pattern.

**Script Preparation Code**

In this case, the script preparation code is provided:
```javascript
var str = "  abc";
var rx = /\\S{3,}/;
```
This code creates two variables: `str`, which contains an input string, and `rx`, which defines a regular expression pattern. The regex pattern `/\\S{3,}/` matches any sequence of whitespace characters (`\S`) that is at least 3 characters long.

**Html Preparation Code**

There is no HTML preparation code provided, which means the benchmark is purely JavaScript-based.

**Test Cases**

The benchmark consists of two test cases:

1. **"trim + length"**: This test case measures the execution time of the expression `str.trim().length > 2`.
2. **"regex test"**: This test case measures the execution time of the expression `rx.test(str)`. Note that this is not a standard JavaScript method, but rather a custom implementation of the regex pattern.

**Library**

In the "regex test" test case, a library is used to implement the regex pattern. The library is not specified in the provided benchmark definition, but based on the code, it appears to be a custom implementation using the `test()` method.

**Special JS Feature/Syntax**

The use of the `\S` character in the regex pattern suggests that this benchmark may utilize Unicode support in JavaScript, which allows for matching non-whitespace characters across different scripts. This is a feature introduced in ECMAScript 2015 (ES6).

**Pros and Cons of Different Approaches**

1. **"trim + length"**: This approach is simple and efficient, as it only requires a single method call to trim the string and then check its length.
	* Pros: easy to implement, low overhead.
	* Cons: may not be suitable for all input strings (e.g., those with null or undefined values).
2. **"regex test"**: This approach uses a custom regex implementation, which can be more complex to set up but provides more flexibility and control over the matching process.
	* Pros: can handle more complex input strings, allows for customization of the matching pattern.
	* Cons: may have higher overhead due to the use of a custom library or implementation.

**Other Alternatives**

If you were to rewrite this benchmark using alternative approaches, you might consider:

1. Using the `String.prototype.indexOf()` method with a starting index of 2 and a length of 3 to check for sequences of non-whitespace characters.
2. Implementing a custom string scanning algorithm that iterates through the input string character by character to detect sequences of non-whitespace characters.

Keep in mind that these alternatives may have different performance characteristics, depending on the specific use case and requirements of your benchmark.

Related benchmarks:

trim + length VS regex with prepared rx (version: 0)

"does the input contain at least 3 non whitespace characters in sequence?"

Comparing performance of: trim + length vs regex test

Created: 4 years ago by: Guest

Jump to the latest result

trim + length

regex test

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):