* The From Nand to Teris project, The Elements of Computing Systems: Building a Modern Computer from First Principles book, and/or Coursera course. Builds a hardware stack for a CPU and then a software stack (assembler, VM, high-level language).
* The How to Design Programs book. What the edX course above is based upon.
* Structure and Interpretation of Computer Programs (SICP). Uses Scheme. One can use Racket with the `#lang sicp` language.
YouTube playlist of the course by the authors: https://youtube.com/playlist?list=PLE18841CABEA24090
* Thinking as Computation: A First Course. Uses Prolog to solve problems of thinking.
* Turtle Geometry: The Computer as a Medium for Exploring Mathematics (shares an author with SICP). Uses Logo to explore turtle geometry/graphics. Can use any modern Logo implementation.
* Starting Forth. Uses Forth.
The author's YouTube channel: https://youtube.com/c/TheCodingTrain
In my experience with FP you start with more of a top down approach in contrast to the bottom up approach discussed in the blog post.
There are many good resources on this. I've referenced a few below. Of course there are many more.
> Have you read SICP? https://www.amazon.com/Structure-Interpretation-Computer-Pro...
However, maybe I'm not very smart and feel like I might have a very hard time with it. I'm not that great at math I don't think, nor do I consider myself genius like. Did people who go through this book do every single problem and figure it out themselves? There are a lot more problems then I expected. They are also, so far, some to be quite challenging and math heavy. It does really feel like it helps get my brain thinking differently about a lot of problems and I love it! But it also feels like I might start grinding a lot and burn out on it. Any tips or help or suggestions how to get through it successfully, get a good amount of education out of, and continue to be excited to keep moving forward?
I know it's free online, but I wanted a physical edition.
Or if you want made of dead trees:
I can't recommend it enough. If you read it, do the exercises, don't limit to read through them.
Maybe it's even better if you start with this, and THEN read the books on algorithms and data structures.
Enjoy your journey!
A Pattern Language, Alexander and Ishikawa and Silverstein http://amzn.to/2s9aSSc
Advanced Programming in the Unix Environment , Stevens http://amzn.to/2qPOMjN
Algorithmics: the Spirit of Computing, Harel http://amzn.to/2rW5FNS
Applied Crytography, Wiley http://amzn.to/2rsULxS
Clean Code, Martin http://amzn.to/2sIOWtQ
Clean Coder, Martin http://amzn.to/2rWgbEP
Code Complete, McConnel http://amzn.to/2qSUIwE
Code: The Hidden Language of Computer Hardware and Software, Petzold http://amzn.to/2rWfR9d
Coders at Work, Seibel http://amzn.to/2qPCasZ
Compilers: Principles, Techniques, & Tools, Aho http://amzn.to/2rCSUVA
Computer Systems: A Programmer's Perspective, O'Hallaron and Bryant http://amzn.to/2qPY5jH
Data Flow Analysis: Theory and Practice, Khedker http://amzn.to/2qTnSvr
Dependency Injection in .NET, Seemann http://amzn.to/2rCz0tV
Domain Driven Design, Evans http://amzn.to/2sIGM4N
Fundamentals of Wireless Communication, Tse and Viswanath http://amzn.to/2rCTmTM
Genetic Programming: An Intrduction, Banzhaf http://amzn.to/2s9sdut
Head First Design Patterns, O'Reilly http://amzn.to/2rCISUB
Implementing Domain-Driven Design, Vernon http://amzn.to/2qQ2G5u
Intrduction to Algorithms, CLRS http://amzn.to/2qXmSBU
Introduction to General Systems Thinking, Weinberg http://amzn.to/2qTuGJw
Joy of Clojure, Fogus and Houser http://amzn.to/2qPL4qr
Let over Lambda, Hoyte http://amzn.to/2rWljcp
Operating Systems: Design and Implementation, Tanenbaum http://amzn.to/2rKudsw
Parsing Techniques, Grune and Jacobs http://amzn.to/2rKNXfn
Peopleware: Productive Projects and Teams, DeMarco and Lister http://amzn.to/2qTu86F
Programming Pearls, Bentley http://amzn.to/2sIRPe9
Software Process Design: Out of the Tar Pit, McGraw-Hill http://amzn.to/2rVX0v0
Software Runaways, Glass http://amzn.to/2qT2mHn
Sorting and Searching, Knuth http://amzn.to/2qQ4NWQ
Structure and Interpretation of Computer Programs, Abelson and Sussman http://amzn.to/2qTflsk
The Art of Unit Testing, Manning http://amzn.to/2rsERDu
The Art of Unix Programming, ESR http://amzn.to/2sIAXUZ
The Design of Design: Essays from a Computer Scientist, Brooks http://amzn.to/2rsPjev
The Effective Engineer, Lau http://amzn.to/2s9fY0X
The Elements of Style, Strunk and White http://amzn.to/2svB3Qz
The Healthy Programmer, Kutner http://amzn.to/2qQ2MtQ
The Linux Programming Interface, Kerrisk http://amzn.to/2rsF8Xi
The Mythical Man-Month, Brooks http://amzn.to/2rt0dAR
The Practice of Programming, Kernighan and Pike http://amzn.to/2qTje0C
The Pragmatic Programmer, Hunt and Thomas http://amzn.to/2s9dlvS
The Psychology of Computer Programming, Weinberg http://amzn.to/2rsPypy
Transaction Processing: Concepts and Techniques, Gray and Reuter http://amzn.to/
Types and Programming Languages, Pierce http://amzn.to/2qT2d6G
Understanding MySQL Internals, Pachev http://amzn.to/2svXuFo
Working Effectively with Legacy Code, Feathers http://amzn.to/2sIr09R
Zen of graphics programming, Abrash http://amzn.to/2rKIW6Q
I'd also learn SICP: https://www.amazon.com/Structure-Interpretation-Computer-Pro...
and algorithms from either CLRS https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press... or Skiena Algorithm Design https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena...
I found The New Turing Omnibus to give a really nice overview of a bunch of topics, some chapters were a lot harder to follow than others but I got a lot from it.
Code by Charles Petzold is a book I recommend to anyone who stays still long enough; it's a brilliant explanation of how computers work.
Structure and Interpretation of Computer Programs (SICP) comes up all the time when this kind of question is asked and for good reason; it's definitely my favourite CS/programming book, and it's available for free online.
I'm still a long way off having the kind of education someone with a CS degree would have but those are my recommendations. I'd love to hear the views of someone more knowledgable.
I personally learned with SICP (But reading this book isn't just about interpreter, it will make you a better programmer and blow your mind in so many different ways. I wouldn't say it's for experts only, but this isn't the kind of book that beginners would get excited about. However, if someone is serious about improving as a developer, I can't think of a better book):
Finally, (How to Write a (Lisp) Interpreter (in Python)) by norvig is a great read if you're getting started with interpreter: http://norvig.com/lispy.html
* The reason the two last links are lisp related is because writing interpreter in Lisp is really straightforward (Since the code is the AST). Similarly, if you wanted to learn about memory management, a language like assembler or C might be more suited than say Python.
https://github.com/onetrueawk/awk - UNIX philosophy of small tools, DSLs, CS theory: state machines / regular expressions, Thompson algorithm ...
https://github.com/mirrors/emacs - Both a program and a VM for a programming language, hooks, before/after/around advices, modes, asynchronous processing with callbacks, ... Worth to think of challenges of designing interactive programs for extensibility.
https://github.com/rails/rails - Metaprogramming DSLs for creating powerful libraries, again a lesson in hooks (before_save etc.), advices (around_filter etc.), ...
https://github.com/git/git - The distributed paradigm, lots of CS theory again: hashing for ensuring consistency, DAGs everywhere, ... By the way, the sentence "yet the underlying git magic sometimes resulted in frustration with the students" is hilarious in the context of a "software architecture" course.
One of computer algebra systems - the idea of a http://en.wikipedia.org/wiki/Canonical_form
One of computer graphics engines - Linear algebra
There are loads of things one can learn from those projects by studying the source in some depth, but I can't think of any valuable things one could learn by just drawing pictures of the modules and connecting them with arrows. There are also several great books that explore real software design issues and not that kind of pretentious BS, they all come from acknowledged all-time master software "architects", yet all of them almost never find diagrams or "viewpoints" useful for saying the things they want to say, and they all walk you through real issues in real programs:
To me, the kind of approach pictured in the post, seems like copying methods from electrical or civil engineering to appear more "serious", without giving due consideration to whether they really are helpful for anything for real-world software engineering or not. The "software engineering" class which taught those kind of diagram-drawing was about the only university class I did not ever get any use from, in fact I had enough industry experience by the point I took it that it just looked silly.
Back when he was still doing podcasts Joel Spolsky answered the similar question, which was partly "Does a good programmer without a CS degree really have a chance to get a job at Fogcreek?" (It's near the end of the page.)
He says that for a good self-taught programmer who began with a high-level language, say PHP or Java, who comes at programming from a practical perspective, there are a few important parts of the CS curriculum the person may have missed out on, and goes on to list some books that would help fill in those gaps.
Off the top of his head he named these books in about this order:
- Structure and Interpretation of Computer Programs (also free online)
- C Programming Language
- The Unix Programming Environment
- Introduction to Algorithms
He said that those books covered the aspects of the CS curriculum his company needs in a good programmer, e.g. being able to create algorithms for an uncommon data structure.
Those books all have the added advantage of having exercises, and all being a very pleasant read. SICP is an introduction to many of the big ideas in CS: data structures, streams, recursion, interpretation, compilation, register machines, etc., and their implementation in Scheme (a kind of Lisp). It's a great place to start. The next two focus on implementation details like pointers and memory allocation. They are compact, powerful books. The last, Introduction to Algorithms, seems misleadingly titled, as it is fairly comprehensive and used in both undergraduate and graduate courses. If you work your way through the entire book, chapeau!
include a few quite accessible books (and several more that are very hard).
How about guidance into C via The Art and Science of C: A Library Based Introduction to Computer Science by Eric S. Roberts
or guidance into LISP with the famous Structure and Interpretation of Computer Programs (SICP) textbook?
What is the difference between the two? The links are:
$115.44 : http://www.amazon.com/Structure-Interpretation-Computer-Prog...
$69.34 : http://www.amazon.com/Structure-Interpretation-Computer-Prog...
Aside from price, the only difference that I can make out is that the cover for the more expensive version is a lighter shade of blue. What it looks like is that Amazon is charging a lot more if you buy SICP as a textbook rather than as a regular book.
Check out the reviews at amazon.com: both PG and some Peter Norvig give you permission to read it:
Or yes, you can choose to postpone the important for the urgent. But for your deity of choice's sake, don't multitask at this. Whenever you think you're ready, get a paper copy and set aside some time for it every day. Kiss the cover. Open the book. Read at least one subsection and do the exercises. Close the book and kiss the cover again. Candles optional.
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