Added a loop that runs the benchmark for different values of N

[JL102]

I also sorted (ha) each algorithm based on their general complexity, so that folks who wanna run it can quickly comment out slower algos so that they can test faster ones with better values of N.

Interestingly, on my system, Merge sort gets really bad at 1,000,000 elements with its large amount of memory usage, and the custom quick sort performs better than JS sort!

[JL102]

more interesting results. Comparison between nodejs and bun with 1,000,000 elements.

Node:

┌─────────┬─────────────┬────────────────────┐
│ (index) │    name     │        time        │
├─────────┼─────────────┼────────────────────┤
│    0    │ 'quickSort' │ 75.02510000765324  │
│    1    │ 'heapSort'  │ 184.67769999802113 │
│    2    │ 'shellSort' │ 215.91150000691414 │
│    3    │ 'radixSort' │ 345.7732999920845  │
│    4    │  'jsSort'   │  377.917999997735  │
│    5    │ 'mergeSort' │ 227719.7909000069  │
└─────────┴─────────────┴────────────────────┘

Bun:

[
  {
    name: "heapSort",
    time: 160.1846430000005
  }, {
    name: "jsSort",
    time: 178.1277869999999
  }, {
    name: "shellSort",
    time: 221.78199899999981
  }, {
    name: "quickSort",
    time: 264.99975399999994
  }, {
    name: "radixSort",
    time: 840.8059830000002
  }, {
    name: "mergeSort",
    time: 864.977034
  }
]

I find it interesting how Radix does very poorly compared to quicksort and heapsort. It might be something to do with the implementation and the fact that it's using JS and not some native language.