Benchmark: add strings - MeasureThat.net

Tests:

kata solution 1
function add (a, b) { var res = '', c = 0 a = a.split('') b = b.split('') while (a.length || b.length || c) { c += ~~a.pop() + ~~b.pop() res = c % 10 + res c = c > 9 } return res } add('63829983432984289347293874', '90938498237058927340892374089')
my solution
function add(a, b) { let result = ''; let remain = 0; if (b.length > a.length) { [a, b] = [b, a]; } b = [...b]; for (let i = a.length - 1; i >= 0; --i) { const n1 = Number(a[i]); const n2 = Number(b.pop() ?? 0); let sum = n1 + n2 + remain; if (sum > 9) { let temp = sum; sum %= 10; remain = (temp - sum) / 10; } else { remain = 0; } result = sum + result; } if (remain) { result = remain + result; } return result; } add('63829983432984289347293874', '90938498237058927340892374089')

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
kata solution 1
my solution

Fastest: N/A

Slowest: N/A

Latest run results:

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

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**Overview of the Benchmark**

The provided JSON represents a JavaScript benchmark, specifically designed to compare the performance of two different approaches for adding two large strings.

**Benchmark Definition**

The `Benchmark Definition` section provides a brief description of the test case. In this case, it's empty (`"Description": null`). The `Script Preparation Code` and `Html Preparation Code` fields are also empty, indicating that no special setup or HTML is required to run the benchmark.

**Individual Test Cases**

There are two test cases:

1. **Kata Solution 1**: This implementation uses a while loop to iterate through both strings from right to left, adding corresponding characters together and carrying over any overflow.
```javascript
function add(a, b) {
  var res = '';
  a = a.split('');
  b = b.split('');
  while (a.length || b.length || c) {
    c += ~~a.pop() + ~~b.pop();
    res = c % 10 + res;
    c = c > 9;
  }
  return res;
}
```
2. **My Solution**: This implementation uses a for loop to iterate through both strings from right to left, adding corresponding characters together and carrying over any overflow.
```javascript
function add(a, b) {
  let result = '';
  let remain = 0;
  if (b.length > a.length) {
    [a, b] = [b, a];
  }
  b = [...b];
  for (let i = a.length - 1; i >= 0; --i) {
    const n1 = Number(a[i]);
    const n2 = Number(b.pop() ?? 0);
    let sum = n1 + n2 + remain;
    if (sum > 9) {
      let temp = sum;
      sum %= 10;
      remain = (temp - sum) / 10;
    } else {
      remain = 0;
    }
    result = sum + result;
  }
  if (remain) {
    result = remain + result;
  }
  return result;
}
```
**Comparison of Approaches**

The two implementations differ in their use of iteration and handling of overflow:

* **Kata Solution 1**: Uses a while loop with manual indexing, which can lead to slower performance due to the overhead of loop management.
* **My Solution**: Uses a for loop with automatic indexing, which is generally faster since it eliminates the need for manual loop management.

**Pros and Cons**

* **Manual Loop Management**: Kata Solution 1's use of a while loop allows for more control over the iteration process, but requires manual management of indices, leading to slower performance.
* **Automatic Indexing**: My Solution's use of a for loop with automatic indexing is generally faster since it eliminates the need for manual loop management.

**Library and Special Features**

There are no libraries mentioned in the benchmark code. However, both implementations utilize JavaScript features such as:

* **Split()**: used to split strings into arrays of individual characters
* **Number()**: used to convert string values to numeric values
* **??**: used for nullish coalescing operator (returns the first operand if it is not null or undefined, and the second operand otherwise)

**Other Alternatives**

Some possible alternatives for implementing this benchmark include:

* Using a more efficient data structure, such as an array buffer, to store the strings.
* Utilizing parallel processing techniques to take advantage of multiple CPU cores.
* Implementing a different algorithm for adding large numbers, such as using binary arithmetic.

Note that these alternatives may not be relevant or feasible depending on the specific requirements and constraints of the benchmark.

Related benchmarks:

add strings (version: 0)

Comparing performance of: kata solution 1 vs my solution

Created: 2 years ago by: Guest

Jump to the latest result

kata solution 1

my solution

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):