Briefly speaking, the scientific method is the idea that you should formulate a hypothesis about the expected results of an experiment before looking at its actual results. Then compare the actual results to the expected results. In computer science – and software engineering, its applied field – the scientific method seems to be widely neglected though. I read a lot of computer science papers that don’t follow this method and it’s practically absent in software programming (notable exception: TDD).
This doesn’t have to be case. The scientific method works very well even in the lowliest places of programming. The first time I remember consciously thinking about this topic was in college when I – then a TA – watched students step through code in their debugger. Students single-stepped over lines of code, observing what happens. That’s not how debugging works best. Rather, before you step over a line of code, form a hypothesis about what’s going to happen, and check the expected result against the actual result once you stepped over the line.
Outside single-stepping through lines of code, the scientific method works pretty much during all parts of software developments. Making a change to speed up a part of the program? Estimate how much faster the program is going to run; maybe 10%. If the actual result is far off, you need to backtrack to understand why your understanding of the program didn’t align with reality. Same with A/B testing of GUIs. Is a round button or a rectangular going to lead to more click-throughs? Don’t just test it and see what happens. First, formulate a hypothesis how many more click-throughs you expect from the button change. If the observed user behavior is far off, you don’t understand your users and need to backtrack.