Great read. A lot hard earned wisdom!
Systems that defy detailed understanding
11–20 of 65 posts
Re: Systems that defy detailed understanding
#12I think this is useful even for systems (SW stacks) that are much smaller and "knowable": you start by observing, trying small things, observing more, trying different things, observe more and slowly build a mental model of what is likely happening and where.
His defining characteristic is where you can permanently work around a bug (not know it, but know _of_ it) vs find it, know it, fix it.
Very interesting.
Re: Systems that defy detailed understanding
#13Great article. Recalls Gall's Law[1]. "A complex system that works is invariably found to have evolved from a simple system that worked." Also, TFA invites a question: if handed a big ball of mud, is it riskier to start from scratch and go for something more triumphant, or try to evolve the mud gradually? I favor the former, but am quite often wrong. [1] https://en.m.wikiquote.org/wiki/John_Gall
Yep, my first thought upon reading this was that no discussion of this subject is complete without a perusal of Gall's Systemantics (https://en.wikipedia.org/wiki/Systemantics).
Re: Systems that defy detailed understanding
#14What a long winded article on what has been known to scientists for decades as "emergence". Emergent properties are systems level properties that are not obvious/predictable from properties of individual components. Looking and observing one ant is unlikely to tell you that several of these creatures can build an anthill.
Re: Systems that defy detailed understanding
#15Big balls of mud result from a process that resembles reinforcement learning, in that modifications are made with a goal in mind and with testing to weed out changes that are not satisfactory, but without any correct, detailed theory about how the changes will achieve the goal without breaking anything.
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Re: Systems that defy detailed understanding
#16"Introduction to Cybernetics" W. Ross Ashby http://pespmc1.vub.ac.be/ASHBBOOK.html > ... still the only real textbook on cybernetics (and, one might add, system theory). It explains the basic principles with concrete examples, elementary mathematics and exercises for the reader. It does not require any mathematics beyond the basic high school level. Although simple, the book formulates principles at a high level of a…
Not sure what cybernetics formally means, but apparently it has to do with complexity management
> W. Ross Ashby is one of the founding fathers of both cybernetics and systems theory. He developed such fundamental ideas as the homeostat, the law of requisite variety, the principle of self-organization, and the principle of regulatory models. Many of these insights were already proposed in the 1940's and 1950's, long before the presently propular "complex adaptive systems" approach arrived at very similar conclusions. Whereas the concepts surrounding the complexity movement are often complicated and confused, Ashby's ideas are surprisingly clear and simple, yet deep and universal.
Good link
Re: Systems that defy detailed understanding
#17Great article. Recalls Gall's Law[1]. "A complex system that works is invariably found to have evolved from a simple system that worked." Also, TFA invites a question: if handed a big ball of mud, is it riskier to start from scratch and go for something more triumphant, or try to evolve the mud gradually? I favor the former, but am quite often wrong. [1] https://en.m.wikiquote.org/wiki/John_Gall
Yep, my first thought upon reading this was that no discussion of this subject is complete without a perusal of Gall's Systemantics ( https://en.wikipedia.org/wiki/Systemantics ).
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Re: Systems that defy detailed understanding
#18Big balls of mud result from a process that resembles reinforcement learning, in that modifications are made with a goal in mind and with testing to weed out changes that are not satisfactory, but without any correct, detailed theory about how the changes will achieve the goal without breaking anything.
Sounds like all of Agile, really. One can characterize Agile as a ball-of-mud maintenance process that scales desirably with the amount of mud.
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Re: Systems that defy detailed understanding
#19Great article. Recalls Gall's Law[1]. "A complex system that works is invariably found to have evolved from a simple system that worked." Also, TFA invites a question: if handed a big ball of mud, is it riskier to start from scratch and go for something more triumphant, or try to evolve the mud gradually? I favor the former, but am quite often wrong. [1] https://en.m.wikiquote.org/wiki/John_Gall
> if handed a big ball of mud, is it riskier to start from scratch and go for something more triumphant, or try to evolve the mud gradually?
Reminiscent of Chesterton’s fence. But then, we end up in such a “complex” situation only when one thing can have multiple causes & effects — which is difficult to model correctly in a clean slate formulation.
The simplest solution seems to be to avoid making software that complex in the first place (we can exert far more control than in the physical world).
But then if we think about Peter Naur’s perspective about programming as a mode of theory building (of the domain) (unsurprising, given the basic cybernetics principles such as the law of requisite variety & the good regulator theorem), then the answer seems to be — unless your domain is really complex, think hard before you implement, and keep refactoring as your understanding improves (and truly to pick problem formulations / frameworks / languages which make that feasible. Of course, easier said than done.) The key point is to keep refactoring “continuously“ to match our understanding of the domain, rather than just “adding features”.
Aside: In my experience, software built on a good understanding of the domain will function well, untouched, for a long time — so long as it is suitably decoupled from the less-well-understood parts. The latter kind, though, generates constant churn, while also being an annoying fit. Really brings home the adage “A month in the laboratory can save a day in the library.”
Re: Systems that defy detailed understanding
#20Great article. Recalls Gall's Law[1]. "A complex system that works is invariably found to have evolved from a simple system that worked." Also, TFA invites a question: if handed a big ball of mud, is it riskier to start from scratch and go for something more triumphant, or try to evolve the mud gradually? I favor the former, but am quite often wrong. [1] https://en.m.wikiquote.org/wiki/John_Gall
Yep, my first thought upon reading this was that no discussion of this subject is complete without a perusal of Gall's Systemantics ( https://en.wikipedia.org/wiki/Systemantics ).
> It is offered from the perspective of how not to design systems, based on system engineering failures. The primary precept of treatise is that large complex systems are extremely difficult to design correctly despite best intentions, so care must be taken to design smaller, less-complex systems and to do so with incremental functionality based on close and continual touch with user needs and measures of effectiveness.
I am working on my first game using unity right now and I wholeheartedly agree. Almost all of my effective refactoring is turning interacting systems into standalone chunks that don’t care about the rest of the system
It’s very hard to do. I imagine my 4th game will go far smoother after I figure out what works and what doesn’t