Benchmark: test001 - MeasureThat.net

Script Preparation code:

var s1 = "_azer464 zrt64**g6r4z***898+f888$8$8$8$8$85e8 g884h8****z6h888th nznn**";
var s2 = "______________1_2_3_4_5_6_7_8_9_1_2_3_4_5_6_7_8_9_1_2_3_4_5_6_7_8_98_999____";
var s3 = "jmlkfjsdmglkjsfdlgkjgldsfkgjm";

Tests:

regex01
s1.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,"$1").replace(/^_+/g, "").replace(/_+$/g, ""); s2.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,"$1").replace(/^_+/g, "").replace(/_+$/g, ""); s3.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,"$1").replace(/^_+/g, "").replace(/_+$/g, "");
regex02
s1.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,"$1").replace(/^_+|_+$/g, "") s2.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,"$1").replace(/^_+|_+$/g, "") s3.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,"$1").replace(/^_+|_+$/g, "")

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
regex01
regex02

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided JSON represents a JavaScript benchmarking test case for measuring the performance of regular expression operations on strings. The test consists of two individual test cases, `regex01` and `regex02`, which compare different approaches to processing regular expressions.

**Script Preparation Code Analysis**

The script preparation code defines three variables: `s1`, `s2`, and `s3`. These variables contain strings that will be used as input for the benchmarking tests. The purpose of these strings is not explicitly stated, but they appear to be generated using a mix of characters, numbers, and special characters.

**Html Preparation Code Analysis**

The HTML preparation code is empty (`null`), which suggests that this benchmarking test does not require any HTML-specific processing or rendering.

**Benchmark Definition Analysis**

The benchmark definition for each test case consists of two regular expression operations:

1. `s.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,\"$1\").replace(/^_+/g, \"\").replace(/_+$/g, \"\");`
2. `s.replace(/[^0-9A-Za-z]+/g,'_').replace(/([0-9])(_+)(?=[0-9])/g,\"$1\").replace(/^_+|_+$/g, \"\")`

These operations appear to:

* Replace non-alphanumeric characters with underscores (`_`)
* Remove consecutive underscores (`_`) from the string
* Remove leading or trailing underscores (`_`)

The main difference between `regex01` and `regex02` is that `regex02` uses an additional regular expression operation: `.replace(/^_+|_+$/g, \"\")`. This removes both leading and trailing underscores, while `regex01` only removes them from the middle of the string.

**Library Usage**

There is no explicit library mentioned in the benchmark definition. However, it's possible that some built-in JavaScript functions or modules are being used for regular expression operations.

**Special JavaScript Features/Syntax**

The test does not appear to use any special JavaScript features or syntax beyond regular expressions.

**Pros and Cons of Different Approaches**

Here are some pros and cons of the different approaches:

1. **`regex01`**
	* Pros: Simpler, more efficient
	* Cons: Removes only consecutive underscores from the middle of the string
2. **`regex02`**
	* Pros: More robust, removes leading and trailing underscores as well
	* Cons: Less efficient due to additional regular expression operation

**Alternatives**

If you were to implement a similar benchmarking test, you could consider using different approaches or optimizing the existing ones:

1. Use a more efficient regular expression engine or implementation.
2. Experiment with alternative string processing algorithms or libraries (e.g., `String.prototype.replaceAll`).
3. Add additional test cases or variations to measure performance under different conditions.

Keep in mind that this is just an analysis based on the provided benchmarking test case, and actual optimizations may depend on specific requirements or constraints.

Related benchmarks:

test001 (version: 1)

g

Comparing performance of: regex01 vs regex02

Created: 7 years ago by: Registered User

Jump to the latest result

regex01

regex02

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):