For every problem there is a solution that is simple, neat - and wrong.I think, however, that the more important part of this quote are the words 'problem' and 'solution'. Until you have an understanding of the problem that is correct, it is unlikely that you will come to a solution at all. Avoiding the introduction of gratuitous complexity is not necessary to reaching that understanding, but it sure helps.
That's... literally what I just said? "Achieving correctness is the whole point of making things simple, after all."
If your solution is not simple, it will not be correct or fast.
Correctness may be the end-goal. But correctness is absolute. So it is a bad performance indicator to set as the goal. Yes, we can track bugs. But the absence of open bugs is no guarantee for correctness.I can never say "We are 5% more correct than last week. Keep up the good work!"
Simplicity is a much better goal for the day-to-day work. Because it can be tracked, measured and evaluated for every individual change.
Excellent, so we both agree with the author that correctness is the ultimate point and that simplicity is just a useful tool for achieving correctness. :)
> Simplicity is a much better goal for the day-to-day work. Because it can be tracked, measured and evaluated for every individual change.
How does one purport to measure simplicity?
http://pages.di.unipi.it/boerger/Papers/Methodology/BcsFacs0...
My thinking was like this. The complexity of software is synonmyous with us saying we don't know what it will do on given inputs. As complexity goes up, it gets more unpredictable. That's because of the input ranges, branching, feedback loops, etc. So, a decent measure of complexity might be simplifying all that down to purest form that we can still measure.
The ASM's are a fundamental model of computation basically representing states, transitions, and conditionals making them happen. So, those numbers for individual ASM's and combinations of them might be good indicator of complexity of an algorithm. And note that they can do imperative and functional programming.
What you think of that idea?
It's the other way around. Correctness is obviously the goal (and likely performance too, depending on your use case), but the way to achieve it is through simplicity. So simplicity should be prioritized - as it allows you to ensure correctness.
> if your solution is not simple, it will not be correct or fast.
The point of the article is that "simple" is a prerequisite of "correct" (and "fast").
>> Simplicity is a much better goal for the day-to-day work. Because it can be tracked, measured and evaluated for every individual change.
>How does one purport to measure simplicity?
There's 40 years of research into that. And loads of tools to support dev teams.
You can start here: https://en.wikipedia.org/wiki/Cyclomatic_complexity
Also related are costing models: https://en.wikipedia.org/wiki/COCOMO
http://shape-of-code.coding-guidelines.com/2018/03/27/mccabe...
http://shape-of-code.coding-guidelines.com/2016/05/19/cocomo...
Have you seen a program that comes with a formal proof of correctness? I have. And boy, they are really simple.
The end result can be complicated. But the program is broken up into small, simple, easy-to-understand pieces that are then composed.