by tinktank on 12/13/23, 8:56 PM with 36 comments
by Layvier on 12/13/23, 9:41 PM
by runningmike on 12/13/23, 10:23 PM
I also keep a very sort overview of imho good resources on Problem Solving Methods at https://www.bm-support.org/problem-solving-methods/
by bob1029 on 12/13/23, 11:37 PM
Relational modeling can be the ultimate answer for wrangling complexity. It supports real world messy things like circular dependencies without a hitch. You can achieve the same in OOP, but then go and try to serialize or persist an instance of such a thing... you will find a very unhappy variety of dragon lurking in that stack trace.
by simne on 12/13/23, 11:20 PM
If considering not just software, but engineering or systems overall, best of all I seen is Goldratt, Theory of Constraints (usually named TOC).
Resources (mostly books) are many, they even created their own accounting system and simulation software. For intro good books The Goal (1,2,3), they are for different markets and shows look on different aspect of TOC, and easy to read.
by golfinho23 on 12/13/23, 9:01 PM
by bionhoward on 12/13/23, 10:56 PM
1. Simple Made Easy by Rich Hickey (video https://www.infoq.com/presentations/Simple-Made-Easy/)
2. Thinking in Systems by Donella Meadows (pdf https://wtf.tw/ref/meadows.pdf)
3. Raymond Hettinger’s content about CHUNKING is classic for this (one example video https://youtu.be/UANN2Eu6ZnM?si=TnLLj1CASwubkAS2)
4. The classic tome on Abstraction is Gödel, Escher, Bach: an Eternal Golden Braid, by Doug Hofstadter (https://en.m.wikipedia.org/wiki/Gödel,_Escher,_Bach)
5. Finally, I’ll cut myself at lucky number five by pointing you toward Jüergen (You-Again!) Schmidhuber’s fascinating webpage: https://people.idsia.ch/~juergen/
Honorable mention to Margaret Hamilton’s T-Maps and F-Maps. Use a hierarchical numbered outline.
Zoom in and out of the fractal network. Remember your working memory holds seven (7) concepts, plus or minus two (2) … so chunk size around five (5) or less is ideal for cognitive accessibility.
by riversflow on 12/13/23, 11:13 PM
Anywho, this is arguably the overarching reason Design Rules: The Power of Modularity[1] was written, at least in the abstract way you are asking it.
The book tells you about the process that led to the creation of IBM's System/360, and it shows how a set of patterns and rules have converged in parallel industry sectors. It was honestly one of the most interesting books I've ever read, and that's exactly what it is about. Highly recommend this book to virtually anyone on this board.
[1] ISBN10: 0262024667
by recursivedoubts on 12/13/23, 11:52 PM
by whalesalad on 12/13/23, 10:10 PM
the concepts here are re: functional programming, but they apply to everything tbh.
whether your system is a single monolith or a bunch of microservices, the core ideas hold true: think about your system in the form of actions (mutations), calculations/computations (reads), and data as data.
by valand on 12/13/23, 9:02 PM
by Nidhug on 12/14/23, 8:52 AM
It deals with more than just software, as it can be applied in many systems.
by charlysl on 12/13/23, 11:09 PM
This textbook, an introduction to the principles and abstractions used in the design of computer systems, is an outgrowth of notes written for 6.033 Computer System Engineering over a period of 40-plus years. Individual chapters are also used in other EECS subjects. There is also a web site for the current 6.033 class with a lecture schedule that includes daily assignments, lecture notes, and lecture slides. The 6.033 class Web site also contains a thirteen-year archive of class assignments, design projects, and quizzes.
https://ocw.mit.edu/courses/res-6-004-principles-of-computer...
by max_ on 12/15/23, 5:15 PM
And learn TLA+. The core idea of TLA+ is that any problem, how ever complex can be represented as a state machine i.e a sequence of variables or states that change over time.
It can be used to describe software, hardware and theoretical concepts like consensus algorithms.
I suspect one low hanging fruit for TLA+ is to use it for describing physical phenomena gravity, magnetism, boiling etc. This I haven't seen work using it for that yet.
by waynesonfire on 12/13/23, 10:23 PM
I will never forgive my college professors for not teaching this to me. Many years later, when I discovered SICP on my own, I recognized that my high-school CS teacher wanted expose me to this. I was too young at the time to understand. Bummer.
SICP is about managing complexity.
by sirwhinesalot on 12/14/23, 10:23 AM
Erlang actors excel in part because they are structured in supervision trees. There's that word again.
If you can, structure things as a tree. If it is not possible, make a DAG. Only use arbitrary graphs as a last resort.
This is why so many OO codebases turn into a mess, every object has references to who knows what, forming a complex dependency graph full of action at a distance.
by 3np on 12/13/23, 10:12 PM
You're describing a major part of Software Engineering. Most reasonable university/college SE 101 courses will focus here. Which is to say, if you haven't (or it's been a while), check reading lists for university SE classes and pick the ones that focus on modeling. steer clear of process/agile material.
Commonly used and recommended books would be GoF (if you're not familiar with the patterns already), Code Complete, and The Pragmatic Programmer.
by hiAndrewQuinn on 12/14/23, 11:00 AM
https://hiandrewquinn.github.io/til-site/posts/the-rule-of-f...
by EdwardCoffin on 12/13/23, 10:00 PM
by paulorlando on 12/13/23, 11:01 PM
by o_nate on 12/14/23, 9:25 PM
by swah on 12/14/23, 6:56 PM
by davedx on 12/13/23, 11:38 PM