Benchmark: Square Every Digit (most popular solution on code wars)

Square Every Digit (most popular solution on code wars) (version: 0)

Welcome. In this kata, you are asked to square every digit of a number and concatenate them. For example, if we run 9119 through the function, 811181 will come out, because 92 is 81 and 12 is 1. Note: The function accepts an integer and returns an integer

Comparing performance of: const nums vs random nums

Created: 2 years ago by: Guest

Jump to the latest result

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/react/16.3.0/cjs/react.production.min.js'></script>

Script Preparation code:

function squareDigits(num) {
    return Number(('' + num).split('')
        .map(function(val) {
            return val * val;
        })
        .join(''));
}

Tests:

const nums
squareDigits(3212); squareDigits(2112); squareDigits(0);
random nums
function randint(min, max){ return Math.floor(Math.random() * (max - min + 1)) + min; } for(let i = 1; i <= 100; i++){ let num = randint(1, 10_000_000); let expected = +[...(''+num)].map(x => Math.pow(+x, 2)).join``; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
const nums
random nums

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36

Browser/OS: Chrome 107 on Windows

View result in a separate tab

Test name	Executions per second
const nums	692935.7 Ops/sec
random nums	5272.9 Ops/sec

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

LLMs can make mistakes. Check important info.

**What is being tested on the provided JSON?**

The provided JSON represents two JavaScript microbenchmarks: `Square Every Digit` and `Random Numbers`. The benchmarks are designed to measure the performance of different approaches for squaring digits and generating random numbers.

**Options compared**

In the `Square Every Digit` benchmark, the options being compared are:

1. **String manipulation**: This approach converts the input number to a string, splits it into individual digits, squares each digit using the `*` operator, and then joins them back together using the `join()` method.
2. **Number arithmetic**: This approach uses number arithmetic to square the digits directly without converting the number to a string.

In the `Random Numbers` benchmark, the options being compared are:

1. **Math.random()**: This approach uses the `Math.random()` function to generate random numbers and then calculates the expected result by squaring each digit of the generated number.
2. **String manipulation**: Similar to the first option in the `Square Every Digit` benchmark, this approach converts the input number to a string, splits it into individual digits, squares each digit using the `*` operator, and then joins them back together using the `join()` method.

**Pros and cons of different approaches**

**Square Every Digit (Number arithmetic)**

Pros:

* Faster execution time due to fewer operations
* More efficient use of CPU resources

Cons:

* May not work correctly for negative numbers or non-integer inputs
* Requires careful handling of edge cases, such as zero or single-digit inputs

**Square Every Digit (String manipulation)**

Pros:

* Easier to implement and understand, especially for developers without experience with number arithmetic
* Works correctly for all integer inputs, including negative numbers and zero

Cons:

* Slower execution time due to the overhead of string operations
* May consume more memory due to the creation of temporary strings

**Random Numbers (Math.random())**

Pros:

* Easy to implement and understand, as it leverages a well-known and widely-used library function
* Works correctly for all integer inputs, including negative numbers and zero

Cons:

* Less efficient execution time compared to using number arithmetic
* May not be suitable for applications requiring high-performance random number generation

**Random Numbers (String manipulation)**

Pros:

* Faster execution time due to the efficiency of string operations
* More memory-efficient compared to using `Math.random()`

Cons:

* More complex implementation, especially for developers without experience with string manipulation
* May require careful handling of edge cases, such as non-integer inputs or extremely large numbers

**Other considerations**

* The use of `join()` in the string manipulation approach can lead to performance issues if the input number is very large.
* The use of `Math.random()` in the random numbers benchmark may not provide a truly random output due to the limitations of the browser's random number generator.

**Library and syntax explanations**

In the provided JSON, the React library is used in the HTML preparation code. This suggests that the benchmark is designed to test the performance of JavaScript code running in a web context, potentially with React as a dependency.

There are no special JS features or syntax mentioned in the benchmark definitions or the latest benchmark result. However, it's worth noting that modern browsers may have specific optimizations or restrictions for certain JavaScript features, such as `let` and `const`.

Related benchmarks:

Square Every Digit (most popular solution on code wars) (version: 0)

Welcome. In this kata, you are asked to square every digit of a number and concatenate them. For example, if we run 9119 through the function, 811181 will come out, because 92 is 81 and 12 is 1. Note: The function accepts an integer and returns an integer

Comparing performance of: const nums vs random nums

Created: 2 years ago by: Guest

Jump to the latest result

const nums

random nums

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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