Depends on the available memory and size of the tables. I’ve worked on cases where time to compute didn’t matter as much as shaving off three more bytes did. Large lookup tables would have absolutely killed us compared to running some math.
I’ve seen bubble sort implemented because we had data that said it was faster and was slightly smaller for the exact type data we were sorting and its expected distribution.
I fondly remember the time I hired a QT expert onto an embedded app team and on his first project he imported a sort algorithm from std. He found the system got weird and glitchy, and often crashed.
Yeahhh turns out the algorithm he chose needed to make a copy in memory and the thread he was working in only had 2048 bytes of stack, so larger inputs would corrupt the stack allocated to the next thread. I had to explain to him that we had a full second to complete the math before we had to give back our semaphore, so saving a couple milliseconds on the sort was not a priority. Fun times.
Depends on the available memory and size of the tables. I’ve worked on cases where time to compute didn’t matter as much as shaving off three more bytes did. Large lookup tables would have absolutely killed us compared to running some math.
Good point! Good point.
I’ve seen bubble sort implemented because we had data that said it was faster and was slightly smaller for the exact type data we were sorting and its expected distribution.
I fondly remember the time I hired a QT expert onto an embedded app team and on his first project he imported a sort algorithm from std. He found the system got weird and glitchy, and often crashed.
Yeahhh turns out the algorithm he chose needed to make a copy in memory and the thread he was working in only had 2048 bytes of stack, so larger inputs would corrupt the stack allocated to the next thread. I had to explain to him that we had a full second to complete the math before we had to give back our semaphore, so saving a couple milliseconds on the sort was not a priority. Fun times.