I've been trying to figure out what computer field I want to go into later on in life. College is just around the corner for me and I've considered looking into Computer Engineering, Software Engineering, etc.
Lately, I've been looking into computer security systems and exploitations of such (purely for educational purposes, on my own property). Unfortunately, it seems to me like 99% of the people out there have no idea what they're talking about. Oftentimes, it's just "run this" or "run that" or "you can find a program that will do all that for you" - no one knows how these programs work or what exactly they do.
I find no fun or interest in using something that someone else created simply to call myself a "hacker" as most people do. In fact, I'm not even interested in hacking systems as much as HOW they do it.
My question all comes down to this.
I want to learn the ins, outs, ups, and downs of computers - everything from abstract concepts such as the internet and data transferral, to hardware. I want to know how computers store data (how the bites are organized, etc.) and what processors, etc. actually do. What is WIFI, really? Do computers communicate with light (something I picked up from a magazine that I read on a plane).
I have multiple years of computer/programming experience, but so much of what I know about computers in general is very broad. Computers send packages of information back and forth between one another, each with a header and content. Computers are composed of multiple components, each with their own function (processor, video card, RAM, hard drive(s), etc.), which I have some basic understanding of already. etc. etc. etc.
There is just so much to a computer and I don't know where to start. I'm sure some of my college classes will clear things up for me, but I'm so curious that I want to start learning as much as I can now.
This question is probably all over the place, so please ask me to clarify when necessary. I'm a little jet lagged at the moment, but I tried to write my thoughts in the quickest, most coherent way possible (I could have completely failed in the process, though).
Thanks in advance for any advice!
Justian Meyer
Please, feel free to edit the tags for this question. The current ones are terrible.
EDIT:
All these comments are making me excited :). So much to learn, so much to explore :).
To help you choose which specialization to go into, I would very highly recommend computer engineering(Known as CMPE or CE in college course books). Your classes will take you to everything you just listed, and with electives you can delve deeper into whichever aspects you wish(such as security and networking).
In CMPE you will learn both software(C, C++, and some C#) and then hardware( maybe two electrical engineering classes). Once you get to assembly programming, you will start to learn how the two combine to make up everything else in any computer or embedded system. It will take you down to the bit level of memory, CPU, data buses, I/O, and so many other things. I am just starting to do Digital Design, and its ****ing glorious. From what you described, you will enjoy being a CMPE major greatly.
There's computer science majors and software engineers; there's electrical engineers; but there is no cell phone, GPS, or computer designed without computer engineers!
Structured Computer Organization, Tanenbaum
It is a great book and explains everything from a transistor to a Java virtual machine.
These two helped me understand how the OS and memory in general works.
I believe a lot of things are derived out of these 'simple mechanics.
1.Anatomy of a program in memory
2.Pushing the limits on Windows memory
Steve Gibson of security now has been doing a series of podcasts on computer basics.
http://www.grc.com/securitynow.htm Episode 233 "Let's Design a Computer (part 1)" up to the most recent one "What We'll Do for Speed".
Every other episode he does listener feedback and those are good to listen to too.
a few times (like right now) they interrupted the series if a important security news item comes up (like when that big SSL thing broke a few months ago)
Its a really good show and I recommend starting on 233 and working your way up, then starting over on episode 1. Has also done very good series on how a computer network works and how cryptography works. (Ep 203 will blow your mind when he talks about the Boyer & Moore
method of searching)
Since you are deciding where to go exactly, to be in software development or to become expert in hardware and networking, I would like to point out that in my opinion it is two different occupations and they require two different mindsets. Good hardware experts are usually not good programmers and good programmers almost always not experts in hardware and networking. So I would say don't try to embrace both, stick to one direction which is most suitable to your mindset. To pursue two rabbits would result in catching no one.
#Justian
I see, sorry I somewhat misunderstood you. Desire to understand intricacies of how code gets processed inside of hardware is a very natural one. When in college I was reading the book "How computer works" - it is fairly simple, even somewhat primitive book about general hardware functionality. But it can get you a broad look on the topic.
Another analogy came to mind. Say linguists research internal mechanics of language, but it is neuroscientists who research on how language signals get processed in brain. Two very different occupations. This is not to discourage you from learning hardware though, this is just to underline difference between two realms.
I've noticed that a number of top universities are offering courses where students are taught subjects relating to Computer Graphics for their CS majors. Sadly this is something not offered by my university and something I would really like to get into sometime in the next couple of years.
A couple of the projects I've found from some universities are great, although I'm mostly interested in two things:
Raytracing:
I want to write a Raytracer within the next two years. What do I need to know? I'm not a fantastic programmer yet (Java, C and Prolog are my main languages as of today) but I'm slowly learning every day. Also, my Math background isn't all that great, so any pointers on books to read or advice on writing such a program would be fantastic. I tend to pick these things up pretty quickly so feel free to chuck references at me.
Programming 3D Rendered Models
I've looked at a couple of projects where students have developed models and used them in games. I've made a couple of 2D games with raster images but have never worked with 3D models. What would I need to learn in regards to programming these models? If it helps I used to be okay with 3D Studio Max and Cinema4D (although every single course seems to use Maya), but haven't touched it in about four years.
Sorry for posting such vague and, let's be honest, stupid questions. It's just something I've wanted to do for a while and something that'd be good as a large project for me to develop in my own time.
Related Questions
Literature and Tutorials for Writing a Ray Tracer
I can recommend pbrt, it's a book and a physically-based renderer used to teach computer science graduates. The description of the maths used is nice and clear, and since it is written in the 'literate programming' you can see the appropriate code (in C++) too.
The book "Computer Graphics: Principles and Practice" (known in the Computer Graphics circles as the "Foley-VanDam") is the basic for most computer graphics courses, and it covers the topic of implementing a ray-tracer in much detail. It is quite dated, but it's still the best, afaik, and the basic principles remain the same.
I also second the recommendation for Eric Lengyel's Mathematics for 3D Game Programming and Computer Graphics. It's not as thorough, but it's a wonderful review of the math basics you need for 3D programming, it has very useful summaries at the end of each chapter, and it's written in an approachable, not too scary way.
In addition, you'll probably want some OpenGL or DirectX basics. It's easier to start working with a 3D API, then learn the underlying maths than the opposite (in my opinion), but both options are possible. Just look for OpenGL on SO and you should find a couple of good references as well.
The 2000 ICFP Programming Contest asked participants to build a ray tracer in three days. They have a good specification for a simple ray tracer, and you can get code for the winning entries and some other entries as well. There were entries in a large number of different programming languages. This might be a nice way for you to get started.
The briefest useful answer I can give is that most of the important algorithms can be found in Real-Time Rendering by Tomas Akenine-Möller, Eric Haines, and Naty Hoffman, and the bibliography at the end has references to the necessary maths. Their website has a recommended reading list as well.
The most useful math book I've read on the subject is Eric Lengyel's Mathematics for 3D Game Programming and Computer Graphics. The maths you need most are geometry (obviously) and linear algebra (for dealing with all the matrices).
I took such a class last year, and I believe that the class was wonderful for forcing students to learn the math behind the computer graphics - not just the commands for making a computer do what you want.
My professor has a site located here and it has his lecture notes and problem sets that you can take a look through.
Our final project was indeed a raytracer, but once you know the mathematics behind it, coding (an inefficient one) is trivial.
For a mathematical introduction into these topics, see
http://graphics.idav.ucdavis.edu/education/GraphicsNotes/homepage.html
Check http://www.scratchapixel.com/lessons/3d-basic-lessons/lesson-1-writing-a-simple-raytracer/
This is a very good place to learn about ray tracing and rendering in general.
I am wondering if anyone has any insight into this. I am thinking of going to grad school to get some computer science related degree. I have always been intrigued by people who are working on problems using statistical packages or simulation to solve problems. What would I study to get a good breadth of knowledge of these things? Do they fall into machine learning?
Thanks
My girlfriend is getting a degree in mathematics with an emphasis in Statistics and Operations Research.
She does a lot of work with SAS and other statistical software to maximize certain functions and predict the likelihood of future events. It may be more mathematics then you like, but you might try looking for masters of CS programs with an emphasis in Operations Research or Statistics.
There's a wide range of possible opportunities here. Let me add the following choices:
Physics with a focus on complex networks. This has applications in biology, epidemiology, sociology, finance, and computer science.
A good machine learning program, with statistics, data mining, text analysis, and computational learning theory.
Industrial engineering/operations research, with simulation, reliability, and process control.
I'd be happy to talk further about this, please put questions in comments.
I would assume that your school would offer some actual Statistics courses, probably in the Math department, which you could take to learn all about this.
Study a lot of mathematics, especially probability and statistics. I have a graduate simulation course right now, and I wish I knew more probs/stats stuff.
In Biostatics (at the U of Minnesota), we did a lot of simulation, in areas like Bayesian statistics, genetics, and others. Any strongly analytical program is a good candidate for teaching the skills you want, including: econ, econometrics, agronomics, statistical genetics... etc., etc., :)
While you're waiting, pick up R, Matlab (Octave is the free implementation), or your Turing-Complete language of choice, dig into Wikipedia, and get to work :)
I'd like to second Gregg Lind's recommendation of thinking about statistics in the biological sciences. It's well-funded, there's a lot of interesting work going on (both theoretical and applied!), and you can sound really cool at parties because somehow, someway you can always make some sort of connection from your work back to curing cancer. :)
Seriously though, a lot of great statistical work was done in the early 20th century by people like Haldane, Fiscer and Wright. More recent interesting work has been done on analysis or large data sets, multiple hypothesis testing, and applied machine learning. It's super exciting. Come join us!
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If you could go back in time and tell yourself to read a specific book at the beginning of your career as a developer, which book would it be?
I expect this list to be varied and to cover a wide range of things.
To search: Use the search box in the upper-right corner. To search the answers of the current question, use inquestion:this. For example:
inquestion:this "Code Complete"
Code Complete (2nd edition) by Steve McConnell
The Pragmatic Programmer
Structure and Interpretation of Computer Programs
The C Programming Language by Kernighan and Ritchie
Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein
Design Patterns by the Gang of Four
Refactoring: Improving the Design of Existing Code
The Mythical Man Month
The Art of Computer Programming by Donald Knuth
Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman
Gödel, Escher, Bach by Douglas Hofstadter
Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
Effective C++
More Effective C++
CODE by Charles Petzold
Programming Pearls by Jon Bentley
Working Effectively with Legacy Code by Michael C. Feathers
Peopleware by Demarco and Lister
Coders at Work by Peter Seibel
Surely You're Joking, Mr. Feynman!
Effective Java 2nd edition
Patterns of Enterprise Application Architecture by Martin Fowler
The Little Schemer
The Seasoned Schemer
Why's (Poignant) Guide to Ruby
The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity
The Art of Unix Programming
Test-Driven Development: By Example by Kent Beck
Practices of an Agile Developer
Don't Make Me Think
Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
Domain Driven Designs by Eric Evans
The Design of Everyday Things by Donald Norman
Modern C++ Design by Andrei Alexandrescu
Best Software Writing I by Joel Spolsky
The Practice of Programming by Kernighan and Pike
Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt
Software Estimation: Demystifying the Black Art by Steve McConnel
The Passionate Programmer (My Job Went To India) by Chad Fowler
Hackers: Heroes of the Computer Revolution
Algorithms + Data Structures = Programs
Writing Solid Code
JavaScript - The Good Parts
Getting Real by 37 Signals
Foundations of Programming by Karl Seguin
Computer Graphics: Principles and Practice in C (2nd Edition)
Thinking in Java by Bruce Eckel
The Elements of Computing Systems
Refactoring to Patterns by Joshua Kerievsky
Modern Operating Systems by Andrew S. Tanenbaum
The Annotated Turing
Things That Make Us Smart by Donald Norman
The Timeless Way of Building by Christopher Alexander
The Deadline: A Novel About Project Management by Tom DeMarco
The C++ Programming Language (3rd edition) by Stroustrup
Patterns of Enterprise Application Architecture
Computer Systems - A Programmer's Perspective
Agile Principles, Patterns, and Practices in C# by Robert C. Martin
Growing Object-Oriented Software, Guided by Tests
Framework Design Guidelines by Brad Abrams
Object Thinking by Dr. David West
Advanced Programming in the UNIX Environment by W. Richard Stevens
Hackers and Painters: Big Ideas from the Computer Age
The Soul of a New Machine by Tracy Kidder
CLR via C# by Jeffrey Richter
The Timeless Way of Building by Christopher Alexander
Design Patterns in C# by Steve Metsker
Alice in Wonderland by Lewis Carol
Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
About Face - The Essentials of Interaction Design
Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
The Tao of Programming
Computational Beauty of Nature
Writing Solid Code by Steve Maguire
Philip and Alex's Guide to Web Publishing
Object-Oriented Analysis and Design with Applications by Grady Booch
Effective Java by Joshua Bloch
Computability by N. J. Cutland
Masterminds of Programming
The Tao Te Ching
The Productive Programmer
The Art of Deception by Kevin Mitnick
The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan
Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp
Masters of Doom
Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett
How To Solve It by George Polya
The Alchemist by Paulo Coelho
Smalltalk-80: The Language and its Implementation
Writing Secure Code (2nd Edition) by Michael Howard
Introduction to Functional Programming by Philip Wadler and Richard Bird
No Bugs! by David Thielen
Rework by Jason Freid and DHH
JUnit in Action
K&R
#Juan: I know Juan, I know - but there are some things that can only be learned by actually getting down to the task at hand. Speaking in abstract ideals all day simply makes you into an academic. It's in the application of the abstract that we truly grok the reason for their existence. :P
#Keith: Great mention of "The Inmates are Running the Asylum" by Alan Cooper - an eye opener for certain, any developer that has worked with me since I read that book has heard me mention the ideas it espouses. +1
Discrete Mathematics For Computer Scientists http://ecx.images-amazon.com/images/I/51HCJ5R42KL._SL500_BO2,204,203,200_AA219_PIsitb-sticker-dp-arrow,TopRight,-24,-23_SH20_OU02_.jpg
Discrete Mathematics For Computer Scientists by J.K. Truss.
While this doesn't teach you programming, it teaches you fundamental mathematics that every programmer should know. You may remember this stuff from university, but really, doing predicate logic will improve you programming skills, you need to learn Set Theory if you want to program using collections.
There really is a lot of interesting information in here that can get you thinking about problems in different ways. It's handy to have, just to pick up once in a while to learn something new.
Systemantics: How Systems Work and Especially How They Fail. Get it used cheap. But you might not get the humor until you've worked on a few failed projects.
The beauty of the book is the copyright year.
Probably the most profound takeaway "law" presented in the book:
The Fundamental Failure-Mode Theorem (F.F.T.): Complex systems usually operate in failure mode.
The idea being that there are failing parts in any given piece of software that are masked by failures in other parts or by validations in other parts. See a real-world example at the Therac-25 radiation machine, whose software flaws were masked by hardware failsafes. When the hardware failsafes were removed, the software race condition that had gone undetected all those years resulted in the machine killing 3 people.
One of my personal favorites is Hacker's Delight, because it was as much fun to read as it was educational.
I hope the second edition will be released soon!
Concepts, Techniques, and Models of Computer Programming.
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Extreme Programming Explained: Embrace Change by Kent Beck. While I don't advocate a hardcore XP-or-the-highway take on software development, I wish I had been introduced to the principles in this book much earlier in my career. Unit testing, refactoring, simplicity, continuous integration, cost/time/quality/scope - these changed the way I looked at development. Before Agile, it was all about the debugger and fear of change requests. After Agile, those demons did not loom as large.
Types and Programming Languages by Benjamin C Pierce for a thorough understanding of the underpinnings of programming languages.
alt text http://ecx.images-amazon.com/images/I/51E0Ojkz8iL._BO2,204,203,200_PIsitb-sticker-arrow-click,TopRight,35,-76_AA300_SH20_OU01_.jpg
Database System Concepts is one of the best books you can read on understanding good database design principles.
The practice of programming. By Brian W. Kernighan, Rob Pike.
The style shown here is excellent - the code just speaks for itself, and the whole book follows the KISS principle. Personally not my languages of choice, but still influential to me.
Programming from the ground up. It's free on the internet. This book taught me AT&T asm. It is very easy to read.
Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp by Peter Norvig
I started reading it because I wanted to learn Common Lisp. When I was halfway, I realized this was the greatest book about programming I had read so far.
Definitively Software Craftsmanship
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This book explains a lot of things about software engineering, system development. It's also extremly useful to understand the difference between different kind of product developement: web VS shrinkwrap VS IBM framework. What people had in mind when they conceived waterfall model? Read this and all we'll become clear (hopefully)
#Peter Coulton -- you don't read Knuth, you study it.
For me, and my work... Purely Functional Data Structures is great for thinking and developing with functional languages in mind.
"The World is Flat" by Thomas Friedman.
Excellence in programming demands an investment of mental energy and a dedication to continued learning comparable to the professions of medicine or law. It pays a fraction of what those professions pay, much less the wages paid to the mathematically savvy who head into the finance sector. And wages for constructing code are eroding because it's a profession that is relatively easy for the intelligent and self-disciplined in most economies to enter.
Programming has already eroded to the point of paying less than, say, plumbing. Plumbing can't be "offshored." You don't need to pay $2395 to attend the Professional Plumber's Conference every other year for the privilege of receiving an entirely new set of plumbing technologies that will take you a year to learn.
If you live in North America or Europe, are young, and are smart, programming is not a rational career choice. Businesses that involve programming, absolutely. Study business, know enough about programming to refine your BS detector: brilliant. But dedicating the lion's share of your mental energy to the mastery of libraries, data structures, and algorithms? That only makes sense if programming is something more to you than an economic choice.
If you love programming and for that reason intend to make it your career, then it behooves you to develop a cold-eyed understanding of the forces that are, and will continue, to make it a harder and harder profession in which to make a living. "The World is Flat" won't teach you what to name your variables, but it will immerse you for 6 or 8 hours in economic realities that have already arrived. If you can read it, and not get scared, then go out and buy "Code Complete."
This last year I took a number of classes. I read
The Innovator's Dilemma (disruptive tech)
The Mythical Man Month (managing software)
Crossing the Chasm (startup)
Database Management Systems, The COW Book
Programming C#, The OSTRICH Book
Beginning iPhone Developmen, The GRAPEFRUIT Book
Each book was amazing but the Innovator's Dilemma by Clayton Christensen (1997!!!) is really a fantastic book, and it got me really thinking about the modern software world. The challenge addressed is disruptive technology, and how disk drive companies and non-technical companies are always disrupted by new, game changing technology. It gives one a new perspective when thinking about Google, probably the biggest 'web' company. Why do they have their hands in EVERYTHING? It's because they don't want to have their position disrupted by something new. The preview on google is plenty to get the idea. Read it!
hackers, by Steven Levy.
The personality and way of life must come first. Everything else can be learned.
The Practice of Programming
and
How to solve it by computer
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The Python language was very influential to me, I wish I would have read these book years ago. The beauty and simplicity of the Python language really affected how I wrote code in other languages.
The New Turing Omnibus http://ecx.images-amazon.com/images/I/51HlYd-%2BRwL._BO2,204,203,200_PIsitb-sticker-arrow-click,TopRight,35,-76_AA300_SH20_OU01_.jpg
Really good book. Has a high-level taste of the most important areas of computer science. Yes, CS != programming, but this is still useful to every programmer.
Object Oriented Analysis and Design with Applications by Brady Booch
The Mythical Man-Month by Fred Brooks
http://en.wikipedia.org/wiki/The_Mythical_Man-Month
I think that "The Art of Unix Programming" is an excellent book, by an excellent hacker/brilliant mind as Eric S. Raymond, who tries to make us understand a few principles of software design (simplicity mainly). This book is a must for every programming who is about to start a project under Unix platform.
While I agree that many of the books above are must-reads (Pragmatic Programmer, Mythical Man-Month, Art of Computer Programming, and SICP come to mind immediately), I'd like to go in a slightly different direction and recommend A Discipline of Programming by Edsger Dijkstra. Even though it's 32 years old, the emphasis on "design for verifiability" is highly relevant (even if "verifiability" means "proof" instead "unit tests").
Code Craft by Pete Goodliffe is a good read!
Code Craft http://ecx.images-amazon.com/images/I/51WZ9AEC3GL._SL500_BO2,204,203,200_PIsitb-dp-500-arrow,TopRight,45,-64_OU01_AA240_SH20_.jpg
Martin Fowler's Refactoring: Improving the Design of Existing Code has already been listed. But I will detail why it has impacted me.
The essence of the whole book is about structuring code so that it is simpler to read and understand by humans. It teaches me strongly that the code that I write is meant for my colleagues and successors to consume and possibly learn something good out of it. It inspires me to consciously program in a manner that leaves people praising my name, and not cursing me to damnation for all eternity.
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C++ How to Program It is good for beginner.This is excellent book that full complete with 1500 pages.
Here's an excellent book that is not as widely applauded, but is full of deep insight: Agile Software Development: The Cooperative Game, by Alistair Cockburn.
What's so special about it? Well, clearly everyone has heard the term "Agile", and it seems most are believers these days. Whether you believe or not, though, there are some deep principles behind why the Agile movement exists. This book uncovers and articulates these principles in a precise, scientific way. Some of the principles are (btw, these are my words, not Alistair's):
The hardest thing about team software development is getting everyone's brains to have the same understanding. We are building huge, elaborate, complex systems which are invisible in the tangible world. The better you are at getting more peoples' brains to share deeper understanding, the more effective your team will be at software development. This is the underlying reason that pair programming makes sense. Most people dismiss it (and I did too initially), but with this principle in mind I highly recommend that you give it another shot. You wind up with TWO people who deeply understand the subsystem you just built ... there aren't many other ways to get such a deep information transfer so quickly. It is like a Vulcan mind meld.
You don't always need words to communicate deep understanding quickly. And a corollary: too many words, and you exceed the listener/reader's capacity, meaning the understanding transfer you're attempting does not happen. Consider that children learn how to speak language by being "immersed" and "absorbing". Not just language either ... he gives the example of some kids playing with trains on the floor. Along comes another kid who has never even SEEN a train before ... but by watching the other kids, he picks up the gist of the game and plays right along. This happens all the time between humans. This along with the corollary about too many words helps you see how misguided it was in the old "waterfall" days to try to write 700 page detailed requirements specifications.
There is so much more in there too. I'll shut up now, but I HIGHLY recommend this book!
Masters of doom. As far as motivation and love for your profession go: it won't get any better than what's been described in this book, truthfully inspiring story!