Having been a hobbyist programmer for 3 years (mainly Python and C) and never having written an application longer than 500 lines of code, I find myself faced with two choices :
(1) Learn the essentials of data structures and algorithm design so I can become a l33t computer scientist.
(2) Learn Qt, which would help me build projects I have been itching to build for a long time.
For learning (1), everyone seems to recommend reading CLRS. Unfortunately, reading CLRS would take me at least an year of study (or more, I'm not Peter Krumins). I also understand that to accomplish any moderately complex task using (2), I will need to understand at least the fundamentals of (1), which brings me to my question : assuming I use C++ as the programming language of choice, which parts of CLRS would give me sufficient knowledge of algorithms and data structures to work on large projects using (2)?
In other words, I need a list of theoretical CompSci topics absolutely essential for everyday application programming tasks. Also, I want to use CLRS as a handy reference, so I don't want to skip any material critical to understanding the later sections of the book.
Don't get me wrong here. Discrete math and the theoretical underpinnings of CompSci have been on my "TODO: URGENT" list for about 6 months now, but I just don't have enough time owing to college work. After a long time, I have 15 days off to do whatever the hell I like, and I want to spend these 15 days building applications I really want to build rather than sitting at my desk, pen and paper in hand, trying to write down the solution to a textbook problem.
(BTW, a less-math-more-code resource on algorithms will be highly appreciated. I'm just out of high school and my math is not at the level it should be.)
Thanks :)
This could be considered heresy, but the vast majority of application code does not require much understanding of algorithms and data structures. Most languages provide libraries which contain collection classes, searching and sorting algorithms, etc. You generally don't need to understand the theory behind how these work, just use them!
However, if you've never written anything longer than 500 lines, then there are a lot of things you DO need to learn, such as how to write your application's code so that it's flexible, maintainable, etc.
For a less-math, more code resource on algorithms than CLRS, check out Algorithms in a Nutshell. If you're going to be writing desktop applications, I don't consider CLRS to be required reading. If you're using C++ I think Sedgewick is a more appropriate choice.
Try some online comp sci courses. Berkeley has some, as does MIT. Software engineering radio is a great podcast also.
See these questions as well:
What are some good computer science resources for a blind programmer?
https://stackoverflow.com/questions/360542/plumber-programmers-vs-computer-scientists#360554
Heed the wisdom of Don and just do it. Can you define the features that you want your application to have? Can you break those features down into smaller tasks? Can you organize the code produced by those tasks into a coherent structure?
Of course you can. Identify any 'risky' areas (areas that you do not understand, e.g. something that requires more math than you know, or special algorithms you would have to research) and either find another solution, prototype a solution, or come back to SO and ask specific questions.
Moving from 500 loc to a real (eve if small) application it's not that easy.
As Don was pointing out, you'll need to learn a lot of things about code (flexibility, reuse, etc), you need to learn some very basic of configuration management as well (visual source safe, svn?)
But the main issue is that you need a way to don't be overwhelmed by your functiononalities/code pair. That it's not easy. What I can suggest you is to put in place something to 'automatically' test your code (even in a very basic way) via some regression tests. Otherwise it's going to be hard.
As you can see I think it's no related at all to data structure, algorithms or whatever.
Good luck and let us know
I must say that sitting down with a dry old textbook and reading it through is not the way to learn how to do anything effectively, even if you are making notes. Doing it is the best way to learn, using the textbooks as a reference. Indeed, using sites like this as a reference.
As for data structures - learn which one is good for whatever situation you envision: Sets (sorted and unsorted), Lists (ArrayList, LinkedList), Maps (HashMap, TreeMap). Complexity of doing basic operations - adding, removing, searching, sorting, etc. That will help you to select an appropriate library data structure to use in your application.
And also make sure you're reasonably warm with MVC - i.e., ensure your model is separate from your view (the QT front-end) as best as possible. Best would be to have the model and algorithms working on their own, and then put the GUI on top. Or a unit test on top. Etc...
Good luck!
It's like saying you want to move to France, so should you learn french from a book, and what are the essential words - or should you just go to France and find out which words you need to know from experience and from copying the locals.
Writing code is part of learning computer science. I was writing code long before I'd even heard of the term, and lots of people were writing code before the term was invented.
Besides, you say you're itching to write certain applications. That can't be taught, so just go ahead and do it. Some things you only learn by doing.
(The theoretical foundations will just give you a deeper understanding of what you wind up doing anyway, which will mainly be copying other people's approaches. The only caveat is that in some cases the theoretical stuff will tell you what's futile to attempt - e.g. if one of your itches is to solve an NP complete problem, you probably won't succeed :-)
I would say the practical aspects of coding are more important. In particular, source control is vital if you don't use that already. I like bzr as an easy to set up and use system, though GUI support isn't as mature as it could be.
I'd then move on to one or both of the classics about the craft of coding, namely
The Pragmatic Programmer
Code Complete 2
You could also check out the list of recommended books on Stack Overflow.
Related
I've been tinkering around with code (Basic, Python, C++, PHP, JavaScript) on and off for almost two decades, but have only recently begun to get more "serious" about it (using Java). I can write code to do what I want, but now I want to learn to optimize my programs to run faster (looping through an array for every element in an array can get slow very quickly, etc). What I don't want is to be popping onto this site every 5 minutes for every little question I have. I want to learn to answer my own questions.
That said, what are some good resources for learning algorithm analysis and optimization?
I have a copy of Data Structures and Algorithms in Java (3rd edition) but I feel it's written to mostly be incorporated into a college curriculum and isn't very easy to use sans-professor. The book also has a tendency to over-use abbreviations, making it hard to flip to a particular chapter without having to skim back through the book to understand what each abbreviation stands for.
I do have some knowledge of Calculus, but it's extremely rusty, so I would prefer resources that give more explanation and fewer formulas.
Thank you in advance for all the help you can give!
I can't recommend enough Michael Abrash's "The Zen of Code Optimization". It's easyto read and full of insights. The parts that focus on pre-pentium x86 are dated, but it's real value is the focus on how to think about making code faster.
I believe it's out of print, but you may find a used copy online.
You might start with Skiena's Algorithm Design Manual. The same author also has a book on puzzle-solving called Programming Challenges, which gives you a more entertaining way to get practice with algorithms than slogging through a textbook.
Background:
An art teacher once gave me a design problem to draw a tiger using only 3 lines. The idea being that I study a tiger and learn the 3 lines to draw for people to still be able to tell it is a tiger.
The solution for this problem is to start with a full drawing of a tiger and remove elements until you get to the three parts that are most recognizable as a tiger.
I love this problem as it can be applied in multiple disciplines like software development, especially in removing complexity.
At work I deal with maintaining a large software system that has been hacked to death and is to the point of becoming unmaintainable. It is my job to remove the burdensome complexity that was caused by past developers.
Question:
Is there a set process for removing complexity in software systems - a kind of reduction process template to be applied to the problem?
Check out the book Refactoring by Martin Fowler, and his http://www.refactoring.com/ website.
Robert C. Martin's Clean Code is another good resource for reducing code complexity.
Unfortunately, the analogy with the tiger drawing may not work very well. With only three lines, a viewer can imagine the rest. In a software system, all the detail has to actually be there. You generally can't take much away without removing something essential.
Check out the book Anti-Patterns for a well-written book on the whole subject of moving from bad (or maladaptive) design to better. It provides ways to recover from a whole host of problems typically found in software systems. I would then add support to Kristopher's recommendation of Refactoring as an important second step.
Checkout the book, Working Effectively with Legacy Code
The topics covered include
Understanding the mechanics of software change: adding features, fixing bugs, improving design, optimizing performance
Getting legacy code into a test harness
Writing tests that protect you against introducing new problems
Techniques that can be used with any language or platform—with examples in Java, C++, C, and C#
Accurately identifying where code changes need to be made
Coping with legacy systems that aren't object-oriented
Handling applications that don't seem to have any structure
This book also includes a catalog of twenty-four dependency-breaking techniques that help you work with program elements in isolation and make safer changes.
While intellectually stimulating, the concept of detail removal doesn't carry very well (at least as-is) to software programs. The reason being that the drawing is re-evaluated by a human with it ability to accept fuzzy input, whereby the program is re-evaluated by a CPU which is very poor at "filling the blanks". Another more subtle reason is that programs convey a spaciotemporal narrative, whereas the drawing is essentially spacial.
Consequently with software there is much less room for approximation, and for outright removal of particular sections of the code. Never the less, refactoring is the operational keyword and is sometimes applicable even for them most awkward legacy pieces. This discipline is however part art part science and doesn't have very many "quick tricks" that I know of.
Edit: One isn't however completely helpless against legacy code. See for example the excellent book references provided in Alex Baranosky and Kristopher Johnson's answers. These books provide many useful techniques, but on the whole I remain strong in my assertion that refactoring non-trivial legacy code is an iterative process that requires both art and science (and patience and ruthlessness and gentleness ;-) ).
This is a loaded question :-)
First, how do we measure "complexity"? Without any metric decided apriori, it may be hard to justify any "reduction" project.
Second, is the choice entirely yours? If we may take an example, assume that, in some code base, the hammer of "inheritance" is used to solve every other problem. While using inheritance is perfectly right for some cases, it may not be right for all cases. What do you in such cases?
Third, can it be proved that behavior/functionality of the program did not change due to refactoring? (This gets more complex when the code is part of a shipping product.)
Fourth, you can start with start with simpler things like: (a) avoid global variables, (b) avoid macros, (c) use const pointers and const references as much as possible, (d) use const qualified methods wherever it is the logical thing to do. I know these are not refactoring techniques, but I think they might help you proceed towards your goal.
Finally, in my humble opinion, I think any such refactoring project is more of people issue than technology issue. All programmers want to write good code, but the perception of good vs. bad is very subjective and varies across members in the same team. I would suggest to establish a "design convention" for the project (Something like C++ Coding Standards). If you can achieve that, you are mostly done. The remaining part is modify the parts of code which does not follow the design convention. (I know, this is very easy to say, but much difficult to do. Good wishes to you.)
We are developing software with pattern recognition in video. We have 7 mathematicians who are creating algorithms. Plus we have 2 developers that maintain / develop the application with these algorithms. The problem is that mathematicians are using different development tools to create algorithm like Matlab, C, C++. Also because they are not developers the don't give much concerns for memory management or multi-threading. This one of the reason why the app. has a lot of bugs.
If in your company you have similar situation, how do you deal with it? What's the best tools you can recommend to create algorithms? What communication supposed to be between mathematicians and developers? What's in your opinion the most effective to work with high-level tools?
I am not sure whether you devs are rewriting the mathematician's stuff or if you just have to interface to it so I am not sure if my answer is of any use.
However: I work together with a bunch of phd candidates and postdocs on a machine learning library and am a student myself. In that process, I came to translate a lot of algorithms from python/numpy to C++/blas.
This process can be quite tedious - especially with numerical and stochastic algorithms, it is hard to find bugs.
So here is what I did: Get some sample inputs and calculate the results with the python code. Generate unit tests out of these for C++ and then start coding them in C++.
Checking concrete sample inputs with the outputs is essential in this setting.
I agree with Makach.
Let the guys who are creating the algorithms use the tools that they are most familiar with. Because there are two separate (and equally important) tasks to work on in this project. First, there is the creating of an efficient, elegant and appropriate mathematically sound algorithm, then there is the twistedly difficult task of translating it into CPU-speak. The mathimaticians should focus on their first task, and to make it easier for them, allow them to use the toosl they are comfortable with. In terms of man hours, it is a much more efficient use of their time to write MATLAB code, than it would be to have them learn a new programming language.
Your task is to unearth the (presumably) brilliant mathematics that are buried within the gibberish code.
That part is just a perspective on the problem at hand. Here's the actual answer.
Communication, mutual respect, and teaching/learning.
Communication & Mutual Respect
You must communicate with them often. Work closely with them and ask them questions whenever you come across something you're not sure of. This is much easier when there is mutual respect, which means that if you spend all your time criticizing their coding abilities, then they will be forced to spend all their time criticizing your math abilities. Instead, try quick learning-sessions. ("Lunch & Learn" is a fairly common tactic)
Teaching/Learning
The first and most important piece of wisdom to impart to them is commenting. Have them comment the crap out of their code. Tell them that the comments are much more important than the code quality, and that as long as their comments are right, they can leave the rest up to you guys. Because they can. They don't need to have their code look beautiful, for be the fastest, they just need it to make sense to you guys.
To continue this mutual learning scenario, if you notice some very simple very common mistakes they are making, (nothing NEARLY as complicated as multithreading) just give them a quick heads up. "That way works (or doesn't) but here's a way to do it that is a little different but it will make your lives much much easier." Encourage them to reciprocate by trying to notice which nuances or parts of their algorithms which you and your team are having difficulty with and teach a little tutorial about it.
Once you guys get the communication flowing, you'll find it easier and easier to shape their coding style to what is best for your team, and they will also find it easier to understand why you don't see it the same way they do.
Also, as mentioned by Kekoav, make sure they provide a few fully loaded test cases.
That means for something like
A -> B -> C -> D -> Solution
They would provide you all the values for A, then what it looks like at B, then what it looks like at C and so on. So that you can be certain that not only is it correct at the end, but it's also correct at every step of the way. Try to have them provide examples that are regular, and also a few of them that are unusual, so that you can be certain your code covers edge cases.
I'd recommend the devs spend a few hours getting used to Matlab, especially the Matlab debugger. If their background is CS then they'll already be familiar with vectors and matrices theoretically if not practically. Other than the matrix being the default data structure, Matlab is C-like and easy enough to interpret for translation into another language.
I have been working with a physics professor lately, and have a little experience with this(although admittedly I'm no expert).
I have had to translate a lot of Matlab code into another language. It has been difficult because a lot of(most) of the operations are absent, including when it comes to precision, and working with matrices and vectors. A good math library needs to be found, or created to fit your needs.
The best way that I have found is to do the following:
Get the algorithm to work correctly in the new language.
Create some tests to verify that the algorithm is producing desired output. Have your mathematicians verify that your converted solution in fact works, and that you have covered all bases with your tests.
Then after it is working, and you can trust your tests, optimize the algorithm to be good coding style, have good design and performance characteristics. Use your regression tests to make sure you aren't breaking anything.
I normally start with a verbatim copy of their algorithms into the other language, and then work from there, regardless of if I do a lot of tests.
It is important to get a working copy first, in case the performance is really not an issue and you need to move on to other things and can come back later to make it faster.
This is your job. How you deal with this is what identifies you as a system developer.
Communicate with your colleagues. Draw and explain, have meetings, agree upon and set standards requirements, follow your plans and talk to your project manager. Make sure that your relevant colleagues are joining up on meetings. Have 1-1 talks etc etc
You cannot blame it on the mathematicians for developers creating bugs. It's their job to worry about implementation, not the mathematicians.
I am interesting in the raw (or composite) metrics used to get a handle on how well a person can program in a particular language.
Scenario: George knows a few programming languages and wants to learn "foobar", but He would like to know when he has a reasonable amount of experience in "foobar".
I am really interesting in something broader than just the LOC (lines of code) metric.
My hope for this question is to understand how engineers quantify the programming language experiences of others and if this can be mechanically measured.
Thanks in Advance!
In reply to the previous two posters, I'd guess that there is a way to get a handle on how well a person can program in a particular language: you can test how well someone knows English, or Maths, or Music, or Medicine, or Fine Art, so what's so special about a programming language?
In reply to the OP, I guess the tests must assess:
How well you can program
How well you can use the programming language
Therefore the metrics might be:
What's the goodness of the person's programming (and there are various dimensions of goodness such as bug-free, maintainable, quick/cheap to write, runs quickly, meets user requirements, etc.)?
Does the person use appropriate/idiomatic features of the programming language in question in order to do that good programming?
It would be difficult to make the test 'mechanical', though: most exams that I know of are graded by a human examiner. In the case of programming, part of the test could be graded mechanically (i.e. "does it run?") but part of it ("is it understandable and idiomatic?") is intended to benefit, and is better judged by, other human programmers.
The best indicator of your expertise in a particular language, in my opinion, is how productive you are in it.
Productivity is not just how fast you can work but, importantly, how few bugs you create and how little refactoring/rework is required later on.
For example, if you took two languages you have similar level of experience with, and were (in parallel universes) to build the same system with both, I would say the language you build the system with faster and with fewer defects/design flaws, is the language you have more expertise in.
Sorry it's not a "hard" metric for you, it's a more practical approach.
I don't believe that this can be "mechanically measured". I've thought about this a lot though.
Hang on...
Even the "LOC" of a program is a heavily disputed topic!
(Are we talking about the output of cat *.{h,c} | wc -l or some other mechnanism, for instance? What about blank lines? Comments? Are comments important? Is good code documented?)
Until you've realised how pointless a LOC comparison is, you've no hope of realising how pointless other metrics are.
It's a rather qualitative thing that is rarely measured with any great accuracy. It's like asking "how smart was Einstein?". Certification is one (and a reasonably thorough) quantitative indicator, but even it falls drastically short of identifying "good programmers" as many recruiters discover.
What are you ultimately trying to achieve? General programming aptitude can be more important than language expertise in some situations.
If you are language-focussed, taking on a challenge like Project Euler using that language may be a way to track progress.
How proficient they are in debugging complex problems in that language.
Ask them about projects they have worked on in the past, difficult problems they encountered and how they solved them. Ask them about debugging techniques they have used - you'll be surprised at what you'll hear, and you might even learn something new ;-)
A lot of places have a person or two who is a superstar in their field - the person everyone else goes to when they can't figure out what is wrong with their program. I'm guessing thats the person you are looking for :-)
Facility with a programming language is not enough. What is required is facility with a programming language in the context of a partiular suite of libraries on a particular platform
C++ on winapi on Windows 32bit
C++ on KDE on Linux
C++ on Symbian on a Nokia S60 phone
C# on MS .NET on Windows
C# on Mono on Linux
Within such a context, the measures of competence using the target language on the target platform are as follows:
The ability to express common
patterns succinctly and robustly.
The ability to debug common but subtle bugs like race conditions.
It would be possible to develope a suite of benchmark exercises for a programmer. One might also, once significant samples were available, determine the bell curve for ability. Preparing these things would take literally years and they would rapidly be obsoleted. This (and general tightness) is why organisations don't bother.
It would also be necessary to grade people in both "tool maker" and "tool user" modes. Tool makers are very different people with a much higher level of competence but they are often unsuited to monkey work, for which you really want a tool user.
John
There are a couple of ways to approach your question:
1) If you are interviewing candidates for a particular position requiring a particular language, then the only measure to compare candidates is 'how long has this person been writing in this language.' It's not perfect - it's not even very good - but it's reality. Unless you want to give the candidate a problem, a computer, and a compiler to test them on the spot there's no other measure. And then most programmer-types don't do well in "someone's watching you" scenarios.
2) I interpret your question to be more of 'when can I call MYSELF profecient in a language?' For this I would refer to levels of learning a non-native language: first level is you need to look up words/phrases in a dictionary (book) in order to say or understand anything; second level would be that you can understand hearing the language(or reading code) with only the occasional lookup in your trusted and now well-worn dictionary; third level you can now speak (or write code) with only the occasional lookup; fourth level is where you dream in the language; and the final levels is where fool native speakers into thinking that you're a native speaker also (in programming, other experts would think that you may have helped develop the language syntax).
Note that this doesn't help determine how good of a programmer you are - just like knowing English without having to look up words in the dictionary doesn't show "how gooder you is at writin' stuff" - that's subjective and has nothing to do with a particular language as people that are good at programming are good in any language you give them.
The phrase "a reasonable amount of experience" is dependent upon the language being considered and what that language can be used for.
A metric is the result of a measurement. Stevens (see wikipedia: Level Of Measurement) proposed that measurements use four different scale types: nominal (assigning a label), ordinal (assigning a ranking), interval (ordering the measurements) and ratio (having a non-arbitrary zero starting point). LOC is a ratio measurement. Although far from perfect, I think LOC is a relevant, objective number indicating how much experience you have in a language and can be compared to quantifiable values in the software industry. But, this begs the question: where do these industry values come from?
Personally, I would say that "George" will know that he has a reasonable amount of experience when he has designed, implemented and tested a project, maybe of his own choosing on his personal time on his home computer if need be. For example: database, business application, web page, GUI test tool, etc.
From the hiring managers point of view, I would start off by asking the programmer how good s/he is in the language, but this is not a metric. I have always thought that the best way to measure a persons ability to write programs is to give the programmer several small programming problems that are thought-out in advance and solved in a given amount of time, say, 5 minutes each. I have never objected to this being done to me in job interviews. Several metrics are available: Was the programmer able to solve the problem (yes or no - nominal)? How much time did it take (number of minutes - ratio)? How effective was their approach to solving the problem (good, fair, poor - ordinal)? You learn not only the persons ability to write code, but can observe several subjective things as well, such as their behaviour as they go about solving the problem, the questions s/he asks while solving the problem, the ability to work under pressure, etc, From a "quality" perspective though, remember that people do not like being measured.
Still, I believe there are some good metrics like the McCabe Cyclomatic Metric for cyclomatic complexity or the amount of useful commentary per block of code or even the average amount of code written between two consecutive tests.
I know of no such thing. I don't believe there's concensus on how to quantify experience or what "reasonable" means. Maybe I'll learn something too, but if I do it'll be a great surprise.
This may be pertinent.
I find that testing the ability to debug is a more accurate gauge of programming skill than any test aimed at straightforward programming problems that I have encountered. Given the source for a reasonably sized class or function with a stated (or unstated, in some cases) misbehavior, can the testee locate the problem?
Well, they try that in job interviews. There's no metric, but you can assess a person's abilities through questioning and quizzing.
WTF/s * LOC, smaller is best.
there are none; expertise can only be judged subjectively relative to others, or tested on specifics (which has its own level of inaccuracy)
see what is the fascination with code metrics for more information
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I've had several false starts in the past with teaching myself how to program. I've worked through several books (mostly C and Python), and end up just learning the syntax without feeling as though I could sit down and actually write a program for myself. When I try to look through the source trees of a project on Codeplex or Sourceforge, I never seem to know where to start reading the code -- the dependencies seem to go in all directions.
I feel as though I'm not learning programming the way it's done "on the street," so I figured I'd take a different approach to asking how a newbie should learn how to code. If you had to learn programming all over again, what are the things you wouldn't do? What did you spend time doing that you now know wasted you weeks or months?
Where I see beginners wasting weeks or months is typing at the keyboard. The computer is very responsive and will cheerfully chew up hours of your time in the edit-compile-run cycle. If you are learning you will save many hours if
You plan out your design on paper before you approach a computer. It doesn't matter what design method you pick or if you have never heard of a design method. Just write down a plan while your brain is fully engaged and not distracted by the computer.
When code will not compile or will not produce the right answer, if you can't fix it in five minutes, walk away from the computer. Go think about what's happening. Print out your code and scribble on it until you believe it's right.
These are just devices for helping to implement the simple but difficult old advice to think before you code.
When I was learning, I solved countless problems on the 15-minute walk from the computing center to my home. Sadly, with modern PCs we don't get that 15 minutes :-) If you can learn to take it anyway, you will become a better programmer, faster.
I certainly wouldn't start by looking at "real" software projects. Like you say, it's too hard to know where to start. That's largely because large projects are more about their large-scale design than about the individual algorithms or about program flow; for one thing, you're probably looking at a complex GUI application with multi-threading, etc. There isn't really anywhere to "start" looking at the code.
The best way to learn programming is to have a problem you want (need) to solve, and then going about solving it. But most importantly, WRITE CODE. When you read programming books, do ALL the exercises. Make sure you did them right. There's no substitute for writing code. No substitute for screwing up and then fixing it.
Stack Over F.. wait no, heh.
The biggest time-sinks for me are generally in respect to "finding the best answer." I often find that I will run into a problem that I know how to solve but feel that there is a better solution and go on the hunt for it. It is only hours/days later that I come to my senses and realize that I have 7 instances of Firefox, each containing at least 5 tabs sprawled out across 46" of monitor space that I realize that I've been caught in the black hole that is the pursuit of endless knowledge.
My advice to you, and myself for that matter, is to become comfortable with notion of refractoring. Essentially what this means (incase you are are not familiar with the term) is you come up with a solution for a problem and go with it, even if there is quite likely a better way of doing it. Once you have finished the problem, or even the program, you can then revisit your methodology, study it, and figure out where you can make changes to improve it.
This concept has always been hard for me to follow. In college I preferred to to write a paper once, print, and turn it in. Writing code can be thought of very similarly to writing a paper. Simply putting the pen to the pad and pushing out whats on your mind may work - but when you look back over it with a fresh pair of eyes you will, without question, see something you will wish you had done differently.
I just noticed you talked about reading through source trees of other people's projects. Reading other people's code is a wonderful idea, but you must read more selectively. A lot of open-source code is hard to read and not stuff you should emulate anyway. So avoid reading any code that hasn't been recommended by a programmer you respect.
Hint: Jon Bentley, Brian Kernighan, Rob Pike, and P. J. Plauger, who are all programmers I respect, have published a lot of code worth reading. In books.
The only way to learn how to program is to write more code. Reading books is great, but writing / fixing code is the best way to learn. You can't learn anything without doing.
You might also want to look at this book, How to Design Programs, for more of a perspective on design than details of syntax.
The only thing that I did that wasted weeks or months was worry about whether or not my designs were the best way to implement a particular solution. I know now that this is known as "premature optimization" and we all suffer from it to one degree or another. The right way to learn programming is to solve a problem, measure your solution to make sure it performs good enough, then move on to the next problem. After some time you'll have a pile of problems you've solved, but more importantly, you'll know a programming language.
There is excellent advice here, in other posts. Here are my thoughts:
1) Learn to type, the reasons are explained in this article by Steve Yegge. It will help more than you can imagine.
2) Reading code is generally considered a hard task. So, it is better to get an open source project, compile it, and start changing it and learn that way, rather than reading and trying to understand.
I can understand the situation you're in. Reading through books, even many will not make you programmer. What you need to do is START PROGRAMMING.
Actually programming is a lot like swimming in my opinion, even if you know only a little syntax and even lesser amount of coding techniques, start coding anyway. Make a small application, a home inventory, an expense catalog, a datesheet, a cd cataloger, anything you fancy.
The idea is to get into the nitty-gritties of it. Once you start programming you'll run into real-world problems and your problem solving skills will develop as you combat them. That's how you become a better programmer everyday.
So get into the thick of it, and swim right through... That's how you'll make it.
Good luck
I think this question will have wildly different answers for different people.
For myself, I tried C++ at one point (I was about ten and had already been programming for a while), with a click-and-drag UI builder. I think this was a mistake, and I should have gone straight to C and pointers and such. Because I'm just that kind of person.
In your case, it sounds like you want to be led down the right path by someone and feel a bit timid about jumping in and doing something by yourself. (You've read several books and now you're asking what not to do.)
I'll tell you how I learned: by doing plenty of fun, relatively short projects, steadily growing in difficulty. I began with QBasic (which I think is still a great learning tool) and it was there where I developed most of my programming skills. They have of course been expanded and refined since that time but I was already capable of good design back in those days.
The sorts of projects you could take on depend on your interests; if you're mathematically inclined you might want to try a prime number generator or projecting 3D points onto the screen; if you're interested in game design then you could try cloning pong (easy) or minesweeper (harder); or if you're more of a hacker you might want to make a simple chat program or file encryption software.
Work on these projects on your own, and don't worry about whether you're doing things the "right" way. As long as you get it to work, you've learned many things. Some time after you've completed a project you may want to revisit it and try to do it better, or just see how other people have done that sort of thing.
Given the way you seem to want to be led along, perhaps you should find yourself a mentor.
Do not learn how to use pointers and how to manually manage memory. You mentioned C, and I spent plenty of time trying to fix bugs that were caused by mixing *x and &x. This is evil...
Find some problem to solve, write or draw a sketch of an algorithm solving the problem, then try to write it. Either use Python (which is much more friendly for beginners) or use C with statically allocated memory only. And use books/tutorials. They offer multiple excercises with solutions, so you can compare yours with them and see other approaches.
Once you'll feel that you can actually write something simple, see some book/tutorial for Object Oriented Design. It's not the best the world has to offer, but it might turn out to be intuitive. If not, check the functional programming (like LISP, Scheme or Haskell languages), or programming in logic (like Prolog). Maybe those will suit you better.
Also - find some mate. A person you can talk to about coding, code maintenance and design. Such person is worth even more than a book.
To all C fans: The C language is great, really. It allows memory usage optimization to the extent impossible in high-level languages as Python or Ruby. The compiled code is also very fast, and is the only choice for RTOS, or modern 3D games engine. But this is not a good entry point for a beginner, that's what I believe.
Oh, and good luck to you! And don't be ashamed to ask! If you don't ask, the answer is much harder to find.
Assuming you have decent math skills try http://projecteuler.net/ It presents a series of problems to solve of increasing dificulty that should be solvible by writing short programs. This should give you experience in solving specific problems with out getting lost in the details of open source projects.
After basic language syntax, you need to learn design. Which is hard. This book may help.
I think you should stop thinking you've wasted time so far-- instead I think you're education is just incomplete, and you've taken a step you're not really ready for. It sounds like the books you've read are useful, you're learning the intricacies of the language. It sounds like you're just not accustomed to the tools you'd use then to package that code together so it runs.
Some books cover that focus on topics like language syntax, design patterns, algorithms and data structures will never mention the tools you need to actual apply that information. These books are great but if its all you've touched I think it would explain your situation.
What development environment are you using? If you're developing for windows you really should be proficient with creating projects, adding code, running and debugging in Visual Studio. You can download Visual Studio Express for free from Microsoft.
I recommend looking for tutorial like books that actually step you through the UI of development environment you are using. Look for actual screenshots with dropdown menus. Look at what the tutorials walk you through, and if its something you don't know how to do consider buying that book. Preferably it will have code you can copy'n'paste in, not code you write yourself.
I personally don't like these books as I can anticipate how to do new things in VS based on how I'd do other things. But if you're training is incomplete from a tools-usage perspective this could move you in the right direction.
It is probably harder to find these types of tutorial books for Python or C development. There is an overabundance of them for .Net development though.
As someone who has only been working as a programmer for 6 months, I might not be the best person to help you get going, but since it wasn't that long ago when I knew next to nothing, its quite fresh in my mind.
When I started my current job programming wasn't going to be part of my job description but when the opportunity came up to do some programming on the side, I couldn't pass it up.
I spent about 1 month doing tutorials on About.com's Delphi section. As much as people diss about.com, Zarko Gajic's tutorials were simple to understand and easy to follow. Once I had a basic knack of the language and the IDE, I jumped straight into a project exporting accounting data for a program called "Adept". Took me a while but I got there...
The biggest help for me was taking on a personal project. I developed an IRC bot in Java for a crappy 2D game called Soldat. I learnt a lot by planning out and coding my own project.
Now I'm pretty comfortable with Delphi Pascal, SQL, C# and Java. I think, once you get the hang of one OOP language, you can learn the syntax of another language, and it gets a lot easier to catch on.
Perhaps start with a small existing project, and find some thing within it that handles some core part of what it does - then with a debugger, step through it and follow what it's doing from the point where you ask it to do that thing for you.
This helps you in a number of ways. You start to better grasp all of the various things that are touched by the code as it attempts to complete its request. Also, you learn invaluable debugging techniques which it seems like far too many developers lack - while you can often eventually discover what is wrong either with repeated printf() (or equivalent) calls, if you can debug you can solve issues an order of magnitude faster.
I have found that conceptually, a great mental model for understanding programming in the abstract is a pattern of data flow. When a user manipulates data, how is it altered by a program for digestion and storage? How is it transformed to re-present to the user in a form that makes sense to them? Fundamentally code is about transformation of data, and all code can be broken down into constructs of various sizes whose purpose is to alter data in one way or another, bugs forming around the mismatch between what the programmer was expecting from the data, how high level libraries the coder is using treat the data, and how the data actually arrives. Following code with a debugger helps you fully understand this transformation in action by observing changes as they occur.
Standard answer is to make something; picking an easy language to do it in is good, but not essential. It's more the working out stuff in your own head, fixing it because it won't work, that really teaches you. For me, this always happens when I try my eternal dream projects (games) which I never finish but always learn from.
I think the thing I would avoid is learning a language in isolated snippets that don't really hang together but just teach various facets of a particular language. As others have said, the really hard and important thing is to learn design. I think the best way to do this is through a tutorial that walks you through creating an actual application, teaching design along the way. That way you can learn why certain decisions are made and learn how to accomplish what's needed to implement the design choices.
For example, I found Agile Web Development with Rails to be a really easy way to learn Ruby on Rails, much better than simply reading a Ruby manual or even poking my way around scattered web tutorials.
Another thing that I would avoid is developing code in isolation, that is, not having people look at it as I go along. Getting feedback from a mentor will help keep you on the right track with respect to the choices you are making and the correct use of language idioms.
Find a problem in your life or something you do that you just feel could be more efficient and write a small solution to it. It might just be a single script but you will gain much more confidence in your abilities when you start to see useful results of your work. You will also be more motivated to finish it as you are interested in using the solution. Start simple and small and then gradually move up to bigger projects.
And as your working on a small project, focus on building everything with quality. I think this is lost on some programmers who feel that their software is more impressive if it contains a ton of features but usually those features aren't well done or usable. If you focus on building quality solutions to real problems you'll be a fantastic programmer.
Good luck!
Work on projects/problems that you already know how to solve partially
You should read Mike clark's article : How I Learned Ruby. Essentially, he used the test framework for Ruby to exercise different elemnents of the languages.
I used this technique to learn python and it was very, very helpful. Not only did i learn the language, but I was very proficient in the test framework for Python at the end of the excercise. Once you have the basics you can start reading code and then working on building some larger project.