Benchmark: Number fixing - 3

Script Preparation code:

function rn() {
    return (Math.random() * 1000).toFixed(3)
}

function rx(v) {
    return v.replace(/\.?0+/, '')
}

function rw(v) {
    let r = v
    while (r.endsWith('0')) {
        r = r.slice(0, r.length - 1)
    }
    if (r.endsWith('.')) {
        r = r.slice(0, r.length - 1)
    }
    return r
}

function rw2(v) {
  const rev = v.split('').reverse()
  for (let i = 0; rev[i] === '0' || rev[i] === '.'; i++) {}
  return rev.slice(i).reverse().join('')
}

Tests:

regex
rx(rn())
while
rw(rn())
reversed
rw2(rn())

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
regex
while
reversed

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark is designed to measure the performance of three different approaches for removing trailing zeros from a floating-point number:

1. `rx(v)`: Using regular expressions to remove trailing zeros.
2. `rw(v)`: Using a while loop to repeatedly remove trailing zeros.
3. `rw2(v)`: Using string manipulation to reverse and then re-join the string, effectively removing trailing zeros.

**Comparison**

The benchmark compares the performance of these three approaches on a random number generated by `Math.random() * 1000` and then converted to a fixed-point number using `toFixed(3)`.

**Pros and Cons**

1. **rx(v)**:
	* Pros: Simple, concise, and efficient.
	* Cons: May not work correctly for numbers with multiple trailing zeros or decimal points.
2. **rw(v)**:
	* Pros: Handles numbers with multiple trailing zeros and decimal points.
	* Cons: Can be slower due to the while loop and string manipulation.
3. **rw2(v)**:
	* Pros: Handles numbers with multiple trailing zeros and decimal points, but may be less efficient than `rx(v)` or `rw(v)`.
	* Cons: More complex code can make it harder to maintain.

**Library**

There is no explicit library used in the benchmark. However, the `toFixed(3)` method uses the built-in JavaScript `Number` object and its formatting capabilities.

**Special JS Feature/Syntax**

The benchmark does not explicitly use any special JavaScript features or syntax. However, it relies on the `Math.random()` function to generate a random number, which is a built-in feature of the JavaScript language.

**Other Alternatives**

If you need alternative approaches for removing trailing zeros from floating-point numbers, some options include:

* Using a library like `lodash` or `underscore`, which provide functions for formatting and manipulating numbers.
* Implementing a custom algorithm using bitwise operations or other low-level techniques.
* Using a specialized library or framework that provides optimized implementations for common math operations.

Keep in mind that the choice of alternative approach will depend on your specific use case, performance requirements, and personal preference.

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.75 Safari/537.36

Browser/OS: Chrome 86 on Mac OS X 10.14.6

View result in a separate tab

Test name	Executions per second
regex	1112492.2 Ops/sec
while	1184711.5 Ops/sec
reversed	840293.7 Ops/sec

Related benchmarks:

Number fixing - 3 (version: 0)

Comparing performance of: regex vs while vs reversed

Created: 4 years ago by: Guest

Jump to the latest result

regex

while

reversed

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):