Benchmark: s ds fzzxzx2 - MeasureThat.net

Script Preparation code:

var number = "123456"

Tests:

1
const isNum = /^\d+$/.test(number);
2
const isNum = /\d/g.test(number);
3
const isNum = !isNaN(number) && !isNaN(parseFloat(number));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2
3

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark data and explain what's being tested.

**Benchmark Definition**

The benchmark definition represents a JavaScript function that checks if a given string is a number or not. The `Script Preparation Code` section contains the input string `"123456"`. There are three test cases with different approaches to check if the string is a number:

1. `const isNum = /^\\d+$/.test(number);`: This uses a regular expression (`^\\d+$`) that matches any sequence of digits (`\\d+`) from start (`^`) to end (`$`). If the input string matches this pattern, the function returns `true`.
2. `const isNum = /\\d/g.test(number);`: This also uses a regular expression (`/\\d/g`) but with the `/g` flag, which enables global matching (matching all occurrences in the string). The `\\d` matches any digit.
3. `const isNum = !isNaN(number) && !isNaN(parseFloat(number));`: This checks if the input string can be parsed to a number using `parseFloat`. If the result is not NaN (Not a Number), and the original value is also not NaN, it returns `true`.

**Options Compared**

The three options being compared are:

* **Regular Expressions**: Using regular expressions with specific patterns (`^\\d+$` and `/\\d/g`) to match numbers.
* **isNaN Checking**: Using the `isNaN()` function in combination with `parseFloat()` to check if a string can be parsed to a number.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Regular Expressions**:
	* Pros: Can handle non-numeric characters, flexible pattern matching.
	* Cons: May be slower due to regular expression parsing, may not work as expected for certain input formats (e.g., negative numbers).
2. **isNaN Checking**:
	* Pros: Simple, widely supported, handles negative numbers and NaN values correctly.
	* Cons: May require additional checks for non-numeric characters or edge cases.

**Other Considerations**

When choosing an approach, consider the following factors:

* Performance: If speed is critical, regular expressions might be slower due to parsing overhead. However, with modern JavaScript engines, the difference may not be significant.
* Robustness: isNaN checking can handle more complex scenarios and non-numeric characters.

**Libraries Used**

None are explicitly mentioned in the provided benchmark data. However, if any of the test cases use libraries or external dependencies, it's likely due to specific requirements or optimizations for the test suite.

**Special JS Features or Syntax**

None are explicitly mentioned in the provided benchmark data. The tests seem to focus on basic JavaScript syntax and built-in functions.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36

Browser/OS: Chrome 127 on Windows

View result in a separate tab

Test name	Executions per second
1	7523118.5 Ops/sec
2	7598345.5 Ops/sec
3	1646010.4 Ops/sec

Related benchmarks:

s ds fzzxzx2 (version: 0)

Comparing performance of: 1 vs 2 vs 3

Created: 2 months ago by: Guest

Jump to the latest result

1

2

3

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):