I share his opinion for scientific software. I think this is because it is building an algorithm versus software. I think the coupling and scope are just too di

I share his opinion for scientific software. I think this is because it is building an algorithm versus software. I think the coupling and scope are just too different. If your loop takes billions of iterations on gigabytes of data before returning the wrong answer, how do you debug? Breakpoints are useless because which iteration introduced the fault? The critical paths are long. Watchpoint start after you pauzed. Reverse debugging is to slow for millions of instructions. If you change the code with the REPL (other post) you invalidate your previous calculations too. Stacktraces are useless because you inline everything, and the callgraph is shallow anyways. Performance profiling needs special tools: you know the hotspot, the debugger tells you where, not why. My conclusion: A debugger is good for finding bug in data that moves, not for data that changes. opinion based on: my debug approach changes depending on the error. Prints are always the easiest solution in the scientific parts.