3 ms·

Software errors which are traceable usually get dealt with with ease. The remaining majority are unknown and governed by power law - eg. a bug uncovers a major

Software errors which are traceable usually get dealt with with ease. The remaining majority are unknown and governed by power law - eg. a bug uncovers a major redesign, but there is no time for rewrites so we have to roll along with it, complicating the design until next big rewrite if it ever happens. Power law phenomena are quantitatively untraceable. Averages mean nothing. Ergo software engineering is largely untraceable and better treated as a discovery or research process. To make things efficient, focus on removing impediments and continual simplification, but don't expect to predict much in advance. Unless it is an instance of a previous task, in which case why isn't there a function/library/framework for it yet?

jeffreyrogers 5y ago
This sort of thinking precludes the possibility of ever developing better methods though. And this statistical argument was actually quite common in machine design until people started actually building machines that were more precise than many believed possible. The thesis I linked has examples of arguments analogous to what you're saying for why precision machine design is impossible. Edit: I don't mean to be too harsh, you could be right, but software engineering is a young discipline. Mechanical engineering is much older and it was only recently that precision machine design became possible (and, just as importantly, teachable). I believe software engineering has the potential for a similar change in how it is done, at least for projects that warrant it.