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After coming across the code golf trivia around the site it is obvious people try to find ways to write code and algorithms as short as the possibly can in terms of characters, lines and total size, even if that means writing something like:
//Code by: job
//Topic: Code Golf - Collatz Conjecture
n=input()
while n>1:n=(n/2,n*3+1)[n%2];print n
So as a beginner I start to wonder whether size actually matters :D
It is obviously a very subjective question highly dependent on the actual code being used, but what is the rule of thumb in the real world.
In the case that size wont matter, how come then we don't focus more on performance rather than size?
I hope this does not become a flame war. Good code has many attributes, including:
Solving the use-case properly.
Readability.
Maintainability.
Performance.
Testability.
Low memory signature.
Good user interface.
Reusability.
The brevity of code is not that important in 21st century programming. It used to be more important when memory was really scarce. Please see this question, including my answer, for books referencing the attributes above.
A lot of good answers already about what's important versus what's not. In real life, (almost) nobody writes code like code golf, wtih shortened identifiers, minimal whitespace, and the fewest possible statements.
That said, "more code" does correlate with more bugs and complexity, and "less code" tends to correlate with better readability and performance. So all other things being equal, it's useful to strive for shorter code, but only in the sense of "these simple 30 lines of code do the same as that 100 complex lines of code".
Writing "code golf" solutions are often to do with showing how "clever" you are in getting the job done in the most succinct way even at the expense of readability. Quite often, however, more verbose code including, for example, memoization of function results, can be faster. Code size can matter for performance, smaller blocks of code can fit in the L1 CPU cache but this is an extreme case of optimization and a faster algorithm will most always be better. "Code Golf" code is not like production code - always write for clarity & readability of the solution rather than terseness if anyone, including yourself, ever intend to read that code again.
Whitespace has no effect on performance. So code like that is just silly (or perhaps the golf score was based on the character count?). The number of lines also has no effect, although the number of statements can have an effect. (exception: python, where whitespace is significant)
The effect is complex, however. It's not at all uncommon to discover that you have to add statements to a function in order to improve it's performance.
Still, without knowing anything else, bet that more statements is a larger object file, and a slower program. But more lines doesn't do anything other than make code more readable up to a point (after which adding more lines makes it less readable ;)
I don't believe that Code Golf has any practical significance. In practice, readable code is what counts. Which in itself is a conflicting requirement: readable code should be concise, but still easy to understood.
However, I would like to answer your question yet differently. Usually, there are fast and simple algorithms. However, if the speed is top priority, things can get complex real fast (and the resulting code will be longer). I don't believe that simplicity equals speed.
There are many aspects to performance. Performance can for example be measured by memory footprint, speed of execution, bandwith consumption, framerate, maintainability, supportability and so on. Performance usually means spending as little as possible of the most scarce resource.
When applied to networking, brevity IS performance. If your webserver serves a little javascript snippet on every page, it doesn't exactly hurt to keep the variable names short. Pull up www.google.com and view source!
Some times DRY is not helping performance. An example is that Microsoft has found that they don't want a to loop through an array unless it is bigger than 3 elements.
String.Format has signatures for one, two and three arguments, and then for array.
There are many ways of trading one aspect for another. This is usually called caching.
You can for example trade memory footprint for speed of execution. For example by doing lookup instead of execution. It is just a matter of replacing () with [] in most popular languages. If you plan it so that the spaceship in your game can only go in a fixed number of directions, you can save on trigonometric function calls.
Or you can use a proxy server with a cache for looking up things over a network. DNS servers do this all the time.
Finally, if development team availability is the most scarce resource, clarity of code is the best bet for maintainability performance, even if it doesn't run quite as fast or is quite as interesting or "elegant" in code.
Absolutely not. Code size and performance (however you measure it) are only very loosly connected. To make matter worse whats a neat trick on one chip/compiler/OS may very well be the worse thing you can do in another archictecture.
Its counter-intuitive but a clear well written simple as possible implmentation is often far more efficient than than a devious bag of tricks. Today's optimizing compilers like clear uncomplicated code just as much as humans and complex trickery can cause them to abandon thier best optimizing strategies.
Writing fewer lines of code tends to be better for a bunch of reasons. For example, the less code you have, the less chance for bugs. See for example Paul Graham's essay, "Succinctness is Power"
Notwithstanding that, the level reached by Code Golf is usually far beyond what makes sense. In Code Golf, people are trying to write code that is as short as possible, even if they know that it's less readable.
Efficiency is a much harder thing to decide. I'm guessing that less code is usually more efficient, but there are many cases where this isn't true.
So to answer the real question, why do we even have Code Golf competitions which aim at a low character count, if that's not a very important thing?
Two reasons:
Making code as short as possible means you have to be both clever, and know a language pretty well to find all kinds of tricks. This makes it a fun riddle.
Also, it's the easiest measure to use for a code competition. Efficiency, for example, is very hard to measure, especially using many different languages, especially since some solutions are more efficient in some cases, but less in others (big input vs small). Readability: that's a very personal thing, which often leads to heated debates.
In short, I don't think there is any way of doing Code Golf style competitions without using "shortness of code" as the criterion.
This is from "10 Commandments for Java Developers"
Keep in Mind - "Less is more" is not always better. - Code efficiency is a great thing, but > in many situations writing less lines of code does not improve the efficiency of that code.
This is (probably) true for all programming languages (though in assembly it could be different).
It makes a difference if you're talking about little academic-style algorithms or real software, which can be thousands of lines of code. I'm talking about the latter.
Here's an example where a reasonably well-written program was speeded up by a factor of 43x, and it's code size was reduced by 4x.
"Code golf" is just squeezing code, like cramming undergraduates into a phone booth. I'm talking about reducing code by rewriting it in a form that is declarative, like a domain-specific-language (DSL). Since it is declarative, it maps more directly onto its requirements, so it is not puffed up with code that exists only for implementation's sake. That link shows an example of doing that.
This link shows a way of reducing size of UI code in a similar way.
Good performance is achieved by avoiding doing things that don't really have to be done. Of course, when you write code, you're not intentionally making it do unnecessary work, but if you do aggressive performance tuning as in that example, you'd be amazed at what you can remove.
The point of code golf is to optimise for one thing (source length), at the potential expense of everything else (performance, comprehensibility, robustness). If you accidentally improve performance that's a fluke - if you could shave a character off by doubling the runtime, then you would.
You ask "how come then we don't focus more on performance rather than size", but the question is based on a false premise that programmers focus more on code size than on performance. They don't, "code golf" is a minority interest. It's challenging and fun, but it's not important. Look at the number of questions tagged "code-golf" against the number tagged "performance".
As other people point out, making code shorter often means making it simpler to understand, by removing duplication and opportunities for obscure errors. That's usually more important than running speed. But code golf is a completely different thing, where you remove whitespace, comments, descriptive names, etc. The purpose isn't to make the code more comprehensible.
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 am a hobbyist programmer (started with VBA to make excel quicker) and have been working with VB.NET / C#.NET and am trying to learn ADO.NET.
A facet of programming that has always frustrated me is what does 'good' look like? I am not a professional so have little to compare against. What makes a better programmer?
Is it:
They have a better understanding of
all the objects / classes / methods
in a given language?
Their programs are more efficient?
The design of their programs are much
better in terms of better
documentation, good choice of names
for functions etc.?
Put another way, if I were to look at the code of a professional programmer, what is the first thing that I would notice about their code relative to mine? For example, I read books like 'Professional ASP.NET' by Wrox press. Are the code examples in that book 'world class'? Is that the pinnacle? Would any top-gun programmer look at that code and think it was good code?
The list below is not comprehensive, but these are the things that I thought of in considering your question.
Good code is well-organized. Data and operations in classes fit together. There aren't extraneous dependencies between classes. It does not look like "spaghetti."
Good code comments explain why things are done not what is done. The code itself explains what is done. The need for comments should be minimal.
Good code uses meaningful naming conventions for all but the most transient of objects. the name of something is informative about when and how to use the object.
Good code is well-tested. Tests serve as an executable specification of the code and examples of its use.
Good code is not "clever". It does things in straightforward, obvious ways.
Good code is developed in small, easy to read units of computation. These units are reused throughout the code.
I haven't read it yet, but the book I'm planning to read on this topic is Clean Code by Robert C. Martin.
The first thing you'd notice is that their code follows a consistent coding-style. They always write their structure blocks the same, indent religiously and comment where appropriate.
The second things you'd notice is that their code is segmented into small methods / functions spanning no more than a couple dozen lines at the most. They also use self describing method names and generally their code is very readable.
The third thing you'd notice, after you messed around with the code a little is that the logic is easy to follow, easy to modify - and therefore easily maintainable.
After that, you'll need some knowledge and experience in software design techniques to understand the specific choices they took constructing their code architecture.
Regarding books, I haven't seen many books where the code could be considered "world-class". In books they try mostly to present simple examples, which might be relevant to solving very simple problems but aren't reflective of more complex situations.
Quoting Fowler, summizing readability:
Any fool can write code that a computer can understand.
Good programmers write code that humans can understand.
'nough said.
Personally, I'll have to quote "The Zen of Python" by Tim Peters. It tells Python programmers what their code should look like, but I find that it applies to basically all code.
Beautiful is better than ugly. Explicit is better than
implicit. Simple is better than complex. Complex is better
than complicated. Flat is better than nested. Sparse is
better than dense. Readability counts. Special cases
aren't special enough to break the rules. Although practicality
beats purity. Errors should never pass silently. Unless
explicitly silenced. In the face of ambiguity, refuse the
temptation to guess. There should be one-- and preferably only
one --obvious way to do it. Although that way may not be obvious
at first unless you're Dutch. Now is better than never.
Although never is often better than right now. If the
implementation is hard to explain, it's a bad idea. If the
implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
Code is poetry.
Start from this point of logic and you can derive many of the desirable qualities of code. Most importantly, observe that code is read far more than it is written, hence write code for the reader. Rewrite, rename, edit, and refactor for the reader.
A follow on corollary:
The reader will be you at time n from the code creation date. The payoff of writing code for the reader is a monotonically increasing function of n. A reader looking at your code for the first time is indicated by n == infinity.
In other words, the larger the gap of time from when you wrote the code to when you revisit the code, the more you will appreciate your efforts to write for the reader. Also, anyone you hand your code off to will gain great benefit from code written with the reader as the foremost consideration.
A second corollary:
Code written without consideration for the reader can be unnecessarily difficult to understand or use. When the consideration for the reader drops below a certain threshold, the reader derives less value from the code than the value gained by rewriting the code. When this occurs the previous code is thrown away and, tragically, much work is repeated during the rewrite.
A third corollary:
Corollary two has been known to repeat itself multiple times in a vicious cycle of poorly documented code followed by forced rewrites.
I've been programming for 28 years and I find this a tough question to answer. To me good code is a complete package. The code is cleanly written, with meaningful variable and method names. It has well placed comments that comment the intent of the code and doesn't just regurgitate the code you can already read. The code does what it is supposed to in an efficient manner, without wasting resources. It also has to be written with an eye towards maintainability.
The bottom line though is that it means different things to different people. What I might label as good code someone else might hate. Good code will have some common traits which I think I've identified above.
The best thing you can do is expose yourself to code. Look at other people's code. Open Source projects are a good source for that. You will find good code and bad code. The more you look at it, the better you will recognize what you determine to be good code and bad code.
Ultimately you will be your own judge. When you find styles and techniques you like adopt them, over time you will come up with your own style and that will change over time. There is no person on here that can wave a wand and say what is good and that anything else is bad.
Read the book Code Complete. This explains a lot of ideas about how to structure code and the the reasons for doing so. Reading it should short-circuit your time to aquiring the experience necessary to tell good from bad.
http://www.amazon.com/Code-Complete-Practical-Handbook-Construction/dp/0735619670/ref=pd_bbs_sr_1?ie=UTF8&s=books&qid=1229267173&sr=8-1
Having been programming for nearly 10 years now myself and having worked with others I can say without bias that there is no difference between a good programmer and an average programmers code
All programmers at a competent level:
Comment Correctly
Structure Efficiently
Document Cleanly
I once overheard a co-worker say "I've always been very logical and rational minded. I think that's why I enjoy developing"
That in my opinion, is the mind of an average programmer. One who sees the world in terms of rules and logic and ultimately obeys those rules when designing and writing a program.
The expert programmer, understands the rules, but also their context. This ultimately leads to them coming up with new ideas and implementations, the mark of an expert programmer. Programming is ultimately an art form.
Succinctly put, a good programmer's code can be read and understood.
In my opinion, a good programmer's code is language-agnostic; well-written code can be read and understood in a short amount of time with minimal thinking, regardless of the programming language used. Whether the code is in Java, Python, C++ or Haskell, well-written code is understandable by people who don't even program in that particular language.
Some characteristics of code that is easy to read are, methods that are well-named, absence of "tricks" and convoluted "optimization", classes are well-designed, to name a few. As others have mentioned, coding style is consistent, succinct and straight-forward.
For example, the other day, I was taking a look at the code for TinyMCE to answer one of the questions on Stack Overflow. It is written in JavaScript, a language that I've hardly used. Yet, because of the coding style and the comments that are included, along with the structuring of the code itself, it was fairly understandable, and I was able to navigate through the code in a few minutes.
One book that was quite an eye-opener for me in the regard of reading good programmer's code is Beautiful Code. It has many articles written by authors of various programming projects in various programming languages. Yet, when I read it, I could understand what the author was writing in his code despite the fact that I've never even programmed in that particular language.
Perhaps what we should keep in mind is that programming is also about communication, not only to the computer but to people, so good programmer's code is almost like a well-written book, which can communicate to the reader about the ideas it wants to convey.
Easy to read
easy to write
easy to maintain
everything else is filigree
Good code should be easily understood.
It should be well commented.
Difficult parts should be even better commented.
Good code is readable. You'd have no trouble understanding what the code is doing on the first read through of code written by a good professional programmer.
Rather then repeat everyone else's great suggestions, I will instead suggest that you read the book Code Complete by Steve McConnell
Essentially it is a book packed full of programming best practices for both functionality and style.
[Purely subjective answer]
For me, good code is a form of art, just like a painting. I might go further and say that it's actually a drawing that includes characters, colors, "form" or "structure" of code, and with all this being so readable/performant. The combination of readability, structure (i.e. columns, indentation, even variable names of the same length!), color (class names, variable names, comments, etc.) all make what I like to see as a "beautiful" picture that can make me either very proud or very detestful of my own code.
(As said before, very subjective answer. Sorry for my English.)
I second the recommendation of Bob Martin's "Clean Code".
"Beautiful Code" was highly acclaimed a couple of years ago.
Any of McConnell's books are worth reading.
Perhaps "The Pragmatic Programmer" would be helpful, too.
%
Just wanted to add my 2 cents... comments in your code -- and your code itself, generally -- should say what your code does, now how it does it. Once you have the concept of 'client' code, which is code that calls other code (simplest example is code that calls a method), you should always be most worried about making your code comprehensible from the "client's" perspective. As your code grows, you'll see that this is... uh, good.
A lot of the other stuff about good code is about the mental leaps that you'll make (definitely, if you pay attention)... 99% of them have to do with doing a bit more work now to spare you a ton of work later, and reusability. And also with doing things right: I almost always want to run the other way rather than using regular expressions, but every time I get into them, I see why everybody uses them in every single language I work in (they're abstruse, but work and probably couldn't be better).
Regarding whether to look at books, I would say definitely not in my experience. Look at APIs and frameworks and code conventions and other people's code and use your own instincts, and try to understand why stuff is the way it is and what the implications of things are. The thing that code in books almost never does is plan for the unplanned, which is what error checking is all about. This only pays off when somebody sends you an email and says, "I got error 321" instead of "hey, the app is broke, yo."
Good code is written with the future in mind, both from the programmer's perspective and the user's perspective.
This is answered pretty well in Fowler's book, "Refactoring", It's the absence of all the "smells" he describes throughout the book.
I haven't seen 'Professional ASP.NET', but I'd be surprised if it's better than OK. See this question for some books with really good code. (It varies, of course, but the accepted answer there is hard to beat.)
This seems to be (should be) a FAQ. There is an ACM article about beautiful code recently. There seems to be a lot of emphasis on easy to read/understand. I'd qualifier this with "easy to read/understand by domain experts". Really good programmers tend to use the best algorithms (instead of naive easy to understand O(n^2) algorithms) for any given problems, which could be hard to follow, if you're not familiar with the algorithm, even if the good programmer gives a reference to the algorithm.
Nobody is perfect including good programmers but their code tend to strive for:
Correctness and efficiency with proven algorithms (instead of naive and adhoc hacks)
Clarity (comment for intent with reference to non-trivial algorithms)
Completeness to cover the basics (coding convention, versioning, documentation, unit tests etc.)
Succinctness (DRY)
Robustness (resilient to arbitrary input and disruption of change requests)
i second the recommendation for uncle bob's "clean code". but you may wish to take a look at http://www.amazon.com/Implementation-Patterns-Addison-Wesley-Signature-Kent/dp/0321413091 as i think this deals with your specific question a bit better. good code should leap off the page and tell you what it does/how it works.
Jeff Atwood wrote a nice article about how coders are Typists first reference:
http://www.codinghorror.com/blog/archives/001188.html
When being a typist you always need to be elegant in your work, having strucutre and proper "grammar" is highly important. Now converting this to "programming"-typing would catch the same outcome.
Structure
Comments
Regions
I'm a software engineere which means during my education i've come across many different languages but my programming always "feel" the same, as my writing does on fekberg.wordpress.com, i have a "special" way for typing.
Now programming different applications and in different languages, such as Java, C#, Assembler, C++,C i've come to the "standard" of writing that i like.
I see everything as "boxes" or regions and each region has it's explaining commenting. A region might be "class Person" and inside this Region i have a couple of methods for properties, which i may call "Access Methods" or such and each property and region has it's own explaining commenting.
This is highly important, i always see my code that i do, as "being a part of an api", when creating an API structure and elegance is VERY important.
Think about this. Also read my paper on Communication issues when adapting outsourcing which explains in rough, how bad code can conflict, Enterpret as you like: http://fekberg.wordpress.com/2008/12/14/communication-issues-when-adapting-outsourcing/
Good code is easy to understand, easy to maintain, and easy to add to. Ideally, it is also as efficient as possible without sacrificing other indicators.
Great code to me is something that is simple to grasp yet sophisticated. The things that make you go, "wow, of course, why didn't I think of it that way?". Really good code is not hard to understand, it simply solves the problem at hand in a straight-forward way (or a recursive way, if that is even simpler).
Good code is where you know what the method does from the name. Bad code is where you have to work out what the code does, to make sense of the name.
Good code is where if you read it, you can understand what it's doing in not much more time than it takes to read it. Bad code is where you end up looking at it for ages trying to work out wtf it does.
Good code has things named in such a way as to make trivial comments unnecessary.
Good code tends to be short.
Good code can be reused to do what it does anywhere else, since it doesn't rely on stuff that is really unrelated to its purpose.
Good code is usually a set of simple tools to do simple jobs (put together in well organised ways to do more sophisticated jobs). Bad code tends to be huge multi-purpose tools that are easy to break and difficult to use.
Code is a reflection of a programmer's skills and mindset. Good programmers always have an eye on the future - how the code will function when requirements or circumstances are not exactly what they are today. How scalabale it will be? How convenient it will be when I am not the one maintaining this code? How reusable the code will be, so that someone else doing similar stuff can reuse the code and not write it again. What when someone else is trying to understand the code that I have written.
When a programmer has that mindset, all the other stuff falls in place nicely.
Note: A code base is worked on by many programmers over time and typically there is not a specific designation of code base to a programmer. Hence good code is a reflection of all the company's standards and quality of their workforce.
(I use "he" below because this is the person that I aspire to be, sometimes with success).
I believe that the core of a good programmer's philosophy is that he is always thinking "I am coding for myself in the future when I will have forgotten all about this task, why I was working on it, what were the risks and even how this code was supposed to work."
As such, his code has to:
Work (it doesn't matter how fast code gets to the wrong answer. There's no partial credit in the real world).
Explain how he knows that this code works. This is a combination of documentation (javadoc is my tool of choice), exception handling and test code. In a very real sense, I believe that, line for line, test code is more valuable than functional code if for no other reason than it explains "this code works, this is how it should be used, and this is why I should get paid."
Be maintained. Dead code is a nightmare. Legacy code maintenance is a chore but it has to be done (and remember, it's "legacy" the moment that it leaves your desk).
On the other hand, I believe that the good programmer should never do these things:
Obsess over formatting. There are plenty of IDEs, editors and pretty-printers that can format code to exactly the standard or personal preference that you feel is appropriate. I use Netbeans, I set up the format options once and hit alt-shift-F every now and then. Decide how you want the code to look, set up your environment and let the tool do the grunt work.
Obsess over naming conventions at the expense of human communication. If a naming convention is leading you down the road of naming your classes "IElephantProviderSupportAbstractManagerSupport" rather than "Zookeeper", change the standard before you make it harder for the next person.
Forget that he works as a team with actual human beings.
Forget that the primary source of coding errors is sitting at his keyboard right now. If there's a mistake or an error, he should look to himself first.
Forget that what goes around comes around. Any work that he does now to make his code more accessible to future readers will almost certainly benefit him directly (because who's going to be the first person asked to look at his code? He is).
It works
It has unit tests that prove that it works
The rest is icing...
The best code has a certain elegance that you recognise as soon as you see it.
It looks crafted, with care and attention to detail. It's obviously produced with someone with skill and has an art about it - you could say it looks sculpted and polished, rather than rough and ready.
It's consistent and reads easily.
It's split into small, highly cohesive functions each of which do one thing and do it well.
It's minimally coupled, meaning that dependencies are few and strictly controlled,
usually by...
Functions and classes have dependencies on abstractions rather than implementations.
Ironically the better the programmer the less indispensable he/she becomes because the code produced is better maintainable by anyone (as stated by general consent by Eran Galperin).
My experience tells the opposite is also true. The worse the programmer the more difficult to maintain his/her code is, so more indispensable he/she becomes, since no other soul can understand the riddles produced.
I have a good example :
Read GWT (google web tookit) Source code, you will see that every fool understand it (some english books are harder to read than this code).
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I'm about to start (with fellow programmers) a programming & algorithms club in my high school. The language of choice is C++ - sorry about that, I can't change this. We can assume students have little to no experience in the aforementioned topics.
What do you think are the most basic concepts I should focus on?
I know that teaching something that's already obvious to me isn't an easy task. I realize that the very first meeting should be given an extreme attention - to not scare students away - hence I ask you.
Edit: I noticed that probably the main difference between programmers and beginners is "programmer's way of thinking" - I mean, conceptualizing problems as, you know, algorithms. I know it's just a matter of practice, but do you know any kind of exercises/concepts/things that could stimulate development in this area?
Make programming fun!
Possible things to talk about would be Programming Competitions that either your club could hold itself or it could enter in locally. I compete in programming competitions at the University (ACM) level and I know for a fact that they have them at lower levels as well.
Those kind of events can really draw out some competitive spirit and bring the club members closer.
Things don't always have to be about programming either. Perhaps suggest having a LAN party where you play games, discuss programming, etc could be a good idea as well.
In terms of actual topics to go over that are programming/algorithm related, I would suggest as a group attempting some of these programming problems in this programming competition primer "Programming Challenges": Amazon Link
They start out with fairly basic programming problems and slowly progress into problems that require various Data Structures like:
Stacks
Queues
Dictionaries
Trees
Etc
Most of the problems are given in C++.
Eventually they progress into more advanced problems involving Graph Traversal and popular Graph algorithms (Dijkstra's, etc) , Combinatrics problems, etc. Each problem is fun and given in small "story" like format. Be warned though, some of these are very hard!
Edit:
Pizza and Soda never hurts either when it comes to getting people to show up for your club meetings. Our ACM club has pizza every meeting (once a month). Even though most of us would still show up it is a nice ice breaker. Especially for new clubs or members.
Breaking it Down
To me, what's unique about programming is the need to break down tasks into small enough steps for the computer. This varies by language, but the fact that you may have to write a "for loop" just to count to 100 takes getting used to.
The "top-down" approach may help with this concept. You start by creating a master function for your program, like filterItemsByCriteria();
You have no idea how that will work, so you break it down into further steps:
(Note: I don't know C++, so this is just a generic example)
filterItemsByCritera() {
makeCriteriaList();
lookAtItems();
removeNonMatchingItems();
}
Then you break each of those down further. Pretty soon you can define all the small steps it takes to make your criteria list, etc. When all of the little functions work, the big one will work.
It's kind of like the game kids play where they keep asking "why?" after everything you say, except you have to keep asking "how?"
Linked lists - a classic interview question, and for good reason.
I would try to work with a C subset, and not try to start with the OO stuff. That can be introduced after they understand some of the basics.
Greetings!
I think you are getting WAY ahead of yourself in forcing a specific language and working on specific topics and a curriculum.. It sounds like you (and some of the responders) are confusing "advising a programming club" with "leading a programming class". They are very different things.
I would get the group together, and the group should decide what exactly they want to get out of the club. In essence, make a "charter" for the club. Then (and only then) can you make determinations such as preferred language/platform, how often to meet, what will happen at the meetings, etc.
It may turn out that the best approach is a "survey", where different languages/platforms are explored. Or it may turn out that the best approach is a "topical"one, where there topic changes (like a book club) on a regular basis (this month is pointers, next month is sorting, the following is recursion, etc.) and then examples and discussions occur in various languages.
As an aside, I would consider a "language-agnostic" orientation for the club. Encourage the kids to explore different languages and platforms.
Good luck, and great work!
Well, it's a programming club, so it should be FUN! So I would say dive into some hand on experience right away. Start with explaining what a main() method is,then have students write a hello world program. Gradually improve the hello world program so it has functions and prints out user inputs.
I would say don't go into algorithm too fast for beginners, let them play with C++ first.
Someone mentioned above, "make programming fun". It is interesting today that people don't learn for the sake of learning. Most people want instant gratification.
Teach a bit of logic using Programming. This helps with(and is) problem solving. The classing one I have in my head are guessing games.
Have them make a program that guesses at a number between 0 and 100.
Have them make a black jack clone ... I have done this in basic :-(
Make paper instructions.
Explain the "Fried eggs" story. Ask the auditory what they would do to make themselves fried eggs. Make them note the step they think about. Probably you will receive less than 5 steps algorithm. Then explain them how many steps should be written down if we want to teach a computer to fry eggs. Something like:
1) Go to the Fridge
2) Open the fridge door
3) Search for eggs
4) If there are no eggs - go to the shop to buy eggs ( this is another function ;) )
5) If there are eggs - calculate how many do you need to fry
6) Close the fridge door
7) e.t.c. :)
Start with basics of C - syntax semantics e.t.c, and in parallel with that explain the very basic algorithms like bubble sort.
After the auditory is familiar with structured programming (this could take several weeks or months, depending how often you make the lessons), you can advance to C++ and OOP.
The content in Deitel&Deitel's C++ programming is a decent introduction, and the exercises proposed at the end of each chapter are nice toy problems.
Basically, you're talking about:
- control structures
- functions
- arrays
- pointers and strings
You might want to follow up with an introduction to the STL ("ok, now that we've done it the hard way... here's a simpler option")
Start out by making them understand a problem like for instance sorting. This is very basic and they should be able to relate quite fast. Once they see the problem then present them with the tools/solution to solve it.
I remember how it felt when I first was show an example of merge-sort. I could follow all the steps but what the hell was I for? Make then crave a solution to a problem and they will understand the tool and solution much better.
start out with a simple "hello world" program. This introduces fundamentals such as variables, writing to a stream and program flow.
Then add complexity from there (linked lists, file io, getting user input, etc).
The reason I say start with hello world is because the kid will get to see a running program really quick. It's nearly immediate feedback-as they will have written a running program right from the start.
IMO, Big-O is one of the more important concepts for beginning programmers to learn.
Have a debugging contest. Provide code samples that include a bug. Have a contest to see who can find the most or fastest.
There is an excellent book, How Not to Program in C++, that you could use to start with.
You always learn best from mistakes and I prefer to learn from some else's.
It will also let those with little experience learn by see code, even if the code only almost works.
In addition to the answers to this question, there are certain important topics to cover. Here's an example of how you could structure the lessons.
First Lesson: Terminology and Syntax
Terminology to cover: variable, operator, loop (iteration), method, reserved word, data type, class
Syntax to cover: assignment, operation, if/then/else, for loop, while loop, select, input/output
Second Lesson: Basic Algorithm Construction
Cover a few simple algorithms, involving some input, maybe a for or a while loop.
Third Lesson: More Advanced Algorithm Topics
This is for things like recursion, matrix manipulation, and higher-level mathematics. You don't have to get into too complex of topics, but introduce enough complexity to be useful in a real project.
Final Lesson: Group Project
Make a project that groups can get involved in doing.
These don't have to be single day lessons. You can spread the topics across multiple days.
Pseudocode should be a very first.
Edit: If they are total programming beginners then I would make the first half just about programming. Once you get to a level where talking about algorithms would make sense then pseudocode is really important to get under the nails.
Thanks for your replies!
And how would you teach them actual problem solving?
I know a bunch of students that know C++ syntax and a few basic algorithms, but they can't apply the knowledge they know when they solve real problems - they don't know the approach, the way to transcribe their thoughts into a set of strict steps. I do not talk about 'high-level' approaches like dynamic programming, greedy etc., but about basic algorithmic mindset.
I assume it's just because of the poor learning process they were going through. In other sciences - math, for example - they are really brilliant.
Just because you are familiar with algorithms does not mean you can implement them and just because you can program does not mean you can implement an algorithm.
Start simple with each topic (keep programming separate from designing algorithms). Once they have a handle on each, slowly start to bring the two concepts together.
Wow. C++ is one of the worst possible languages to start with, in terms of the amount of unrelated crap you need to get anything working (Java would be slightly worse, I guess).
When teaching beginners in a boilerplate-heavy environment, it's usual to start with "here's a simple C program. We'll discuss what all this crap at the top of the file is for later, but for now, concentrate on the lines between 'int main(void)' and the 'return' statement, which is where all the useful work is accomplished".
Once you're past that point, basic concepts to cover include the basic data structures (arrays, linked lists, trees, and dictionaries), and the basic algorithms (sorting, searching, etc).
Have your club learn how to actually program in any language by teaching the concepts of building software. Instead of running out an buying a dozen licenses for Visual Studio, have students use compilers, make systems, source files, objects and librarys in order to turn their C code into programs. I feel this is truly the beginning and actually empowers these kids to understand how to make software on any platform, without crutches that many educational institutions like to rely on.
As for the language of choice - congratulations - you'll find C++ is very rich in making you think of mathematical shortcuts and millions of ways to make your code perform even better (or to implement fancy patterns).
To the question: When I was beggining to program I would always try to break down one real life problem into several steps and then as I see similarity between tasks or data they transform I would always try to find a lazier, easier, meanier way to implement it.
Elegance came after when learning patterns and real algorithms.
Hank: Big O??? you mean tell beginning programmers that their code is of O(n^2) and yours is of n log n ??
I could see a few different ways to take this:
1) Basic programming building blocks. What are conditional statements, e.g. switch and if/else? What are repetition statements, e.g. for and while loops? How do we combine these to get a program to be the sequence of steps we want? You could take something as easy as adding up a grocery bill or converting temperatures or distances from metric to imperial or vice versa. What are basic variable types like a string, integer, or double? Also in here you could have Boolean Algebra for an advanced idea or possibly teach how to do arithmetic in base 2 or 16 which some people may find easy and others find hard.
2) Algorithmically what are similar building blocks. Sorting is a pretty simple topic that can be widely discussed and analysed to try to figure out how to make this faster than just swapping elements that seem out of order if you learn the Bubblesort which is the most brain dead way to do.
3) Compiling and run-time elements. What is a call stack? What is a heap? How is memory handled to run a program,e.g. the code pieces and data pieces? How do we open and manipulate files? What is compiling and linking? What are make files? Some of this is simple, but it can also be eye-opening just to see how things work which may be what the club covers most of the time.
These next 2 are somewhat more challenging but could be fun:
4) Discuss various ideas behind algorithms such as: 1) Divide and conquer, 2) Dynamic programming, 3) Brute force, 4) Creation of a data structure, 5) Reducing a problem to a similar one already solved for example Fibonacci numbers is a classic recursive problem to give beginning programmers, and 6) The idea of being, "greedy," like in a making change example if you were in a country where coin denominations where a,b, and c. You could also get into some graph theory examples like a minimum weight spanning tree if you want something somewhat exotic, or the travelling salesmen for something that can be easy to describe but a pain to solve.
5) Mathematical functions. How would you program a factorial, which is the product of all numbers from 1 to n? How would you compute the sums of various Arithmetic or Geometric Series? Or compute the number of Combinations or Permutations of r elements from a set of n? Given a set of points, approximate the polynomial that meets this requirement, e.g. in a 2-dimensional plane called x and y you could give 2 points and have people figure out what are the slope and y intercept if you have solved pairs of linear equations already.
6) Lists which can be implemented using linked lists and arrays. Which is better for various cases? How do you implement basic functions such as insert, delete, find, and sort?
7) Abstract Data Structures. What are stacks and queues? How do you build and test classes?
8) Pointers. This just leads to huge amounts of topics like how to allocate/de-allocate memory, what is a memory leak?
Those are my suggestions for various starting points. I think starting a discussion may lead to some interesting places if you can get a few people together that don't mind talking on the same subject week after week in some cases as sorting may be a huge topic to cover well if you want to get into the finer points of things.
You guys could build the TinyPIM project from "C++ Standard Library from Scratch" and then, when it's working, start designing your own extensions.
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One of the companies required from its prospective employee to give the number of lines of code written in the life time in a certain programming language like Java, or C#. Since, most of us have a number of years of experience in different projects in multiple languages and we hardly keep record of this, what would be the best approach to calculate this metrics. I am sure the smart members of stackoverlow.com will have some ideas.
This is a very respected company in its domain and I am sure they have some very good reason to ask this question. But what makes it also difficult to answer is the type of code to consider. Should I only include the difficult algorithm that I implemented or any code I wrote for e.g. a POJO that had 300 properties and whose getters/setters were generated using IDEs!
The best response to such a question is one of the following:
Why do you want to know?
What meaning would you attribute to such a number?
Is it OK if I just up and leave just about now?
I would seriously question the motives behind anyone asking such a question either of current or prospective employees. It is most likely the same type of company that would start doing code reviews focusing on the number of lines of code you type.
Now, if they argue that the number of lines of code is a measure of the experience of a programmer, then I would definitely leave the interview at that point.
Simple solutions can be found for complex problems, and are typically better than just throw enough lines of code at the problem and it'll sort itself out. Since the number of bugs produced scales linearly and above with the number of statements, I would say that the inverse is probably better, combined with the number of problems they've tackled.
As a test-response, I would ask this:
If in a program I am able to solve problem A, B and C in 1000 lines of code, and another programmer solves the same problems in 500 lines of code, which of us is the best (and the answer would be: not enough information to judge)
Now, if you still want to estimate the number of lines, I would simply start thinking about the projects the person has written, and compare their size with a known quantity. For instance, I have a class library that currently ranges about 130K lines of code, and I've written similar things in Delphi and other languages, plus some sizable application projects, so I would estimate that I have a good 10 million lines of code on my own at least. Is the number meaningful? Not in the slightest.
Sounds like this is D E Shaw's questionnaire?
This seems like one of those questions like 'How many ping-pong balls could you fit in a Boeing 747?' In that case, the questioner wants to see you demonstrate your problem solving skills more than know how many lines of code you've actually written. I would be careful not to respond with any criticism of the question, and instead honestly try to solve the problem ; )
Take a look at ohloh. The site shows metrics from open source projects.
The site estimates that 107,187 lines of code corresponds to an effort of 27 Person Years (4000 lines of code per year).
An example of the silliness of such a metric is that the number is from a project I've been toying with outside work during 2 years.
There are basically three ways of dealing with ridiculous requests for meaningless metrics.
Refuse to answer, challenging the questioner for their reasons and explaining why those reasons are silly.
Spending time gathering all the information you can, and calculating the answer to the best of your ability.
Making up a plausible answer, and moving on with as little emotional involvement possible in the stupidity as possible.
The first answers I see seem to be taking the first line. Think about whether you still want the job despite the stupidity of their demands. If the answer is still Yes, avoid number 1.
The second method would involve looking at your old code repositories from old projects.
In this case, I would go with the third way.
Multiply the number of years you have worked on a language by 200 work days per year, by 20 lines of code a day, and use that.
If you are claiming more than one language per year, apportion it out between them.
If you have been working more on analysis, design or management, drop the figure by three quarters.
If you have been working in a high-ceremony environment (defence, medicine), drop the figure by an order of magnitude.
If you have been working on an environment with particularly low ceremony, increase it by an order of magnitude.
Then put the stupidity behind you and get on with your life as quickly as possible
Depending on what they do with the answer, I don't think this is a bad question. For example, if a candidate puts JavaScript on their resume, I want to know how much JavaScript have they actually written. I may ask, for example, for the number of lines in the largest JavaScript project they've written. But I'm only looking for a sense of scale, not an actual number. Is it 10, 100, 1000, or 10,000 lines?
When I ask, I'll make very clear that I'm just looking for a crude number to gauge the size of the project. I hope the employer in the questioner's case is after the same.
It is an interesting metric to ask for considering you could write many many lines of bad code instead of writing just a few smart ones.
I can only assume they are considering more lines to be better than fewer. Would it be better to not plan at all and just start writing code, That would be a great way to write more lines of code, since at least if I do that I usually end up writing everything at least twice.
Smart of stack overflowers would generally avoid organization that ask this kind of question. Unless the correct answer is "huh, wtf??"
If you were to be truly honest then you'd say that you don't know because you have never viewed it as a valid metric. If the interviewer is a reasonable/rational person, then this is the answer they are looking for.
The only other option to saying you don't know is to guess, and that really isn't demonstrating problem solving skills.
Why bother calculating this metric without a good reason? And some random company asking for the metric really isn't a good reason.
If the company's question is actually serious, and you think the interview might lead to something interesting, then I would just pick a random number in order to see where that leads :-)
Ha, reminds me when I took over a C based testing framework, which started out as 20K+
lines that I ended up collapsing into 1K LOC by factoring down to a subroutine instead
of the 20K lines of diarrea code originally written by the original author. Unfortunately,
I got spanked harder for any errors in the code as my KLOC's written actually went
negative... I would think long and hard about shrinking the code base in a metrics driven organization....
Even if I agree with the majority in saying that this is not a really good metric, if it's a serious compmany, as you say, they may have their reasons to ask this.. This is what I would probably do:
Take one of your existing project, get the number of lines and divide it by the time it took you to code it. This will give you a kind of lines per hour metric. Then, try to estimate how many time you have worked with that specific language and multiply it with your already calculated metric. I honestly don't think it's a great way.. but honest, this isn't a great question neither.. I would also tell the company the strategy I used to come up with this number.. maybe, MAYBE, this is what they want.. to know your opinion about this question and how you would answered it? :p
Or, they just want to know if you have some experiences.. so, guess an impressive number and write it down :D
"This is a very respected company in its domain and I am sure they have some very good reason to ask this question"
And I am very sure they don't, because "being respected" does not mean "they do everything right", because this is certainly not right, or if it is, then it's at least dumb in my opinion.
What does count as "Lines of Code"? I estimate that I have written around 250.000 Lines of C# Code, possibly a lot more. The Problem? 95% was throwaway code, and not all was for learning. I still find myself writing a small 3-line program for the tenth time simply because it's easier to write those three lines again (and change a parameter) than go search for the existing ones.
Also, the lines of code means nothing. So I have two guys, one has written 20% more Lines that the other one, but those 20% more were unnecessary complicated lines, "loop-unrolling" and otherwise useless stuff that could have been refactored out.
So sorry, respected company or not: Asking for Lines of Code is a sure sign that they have no clue about measuring the efficiency of their programmers, which means they have to rely on stone-age techniques like measuring the LoC that are about as accurate as calendars in stone-age. Which means it's possibly a good place to work in if you like to slack off and inflate your Numbers every once in a while.
Okay, that was more a rant than an answer, but I really see absolutely no good reason for this number whatsoever.
And nobody has yet cited the Bill Atkinson -2000 lines story...
In my Friday afternoon (well, about one Friday per month) self-development exercises at work over the past year, tests, prototypes and infrastructure included, I've probably written about 5 kloc. However one project took an existing 25kloc C/C++ application and reimplemented it as 1100 lines of Erlang, and another took 15kloc of an existing C library and turned it into 1kloc of C++, so the net is severely negative. And the only reason I have those numbers was that I was looking to see how negative.
I know this is an old post, but this might be useful to someone anyway...
I recently moved on from a company I worked at for roughly 9.5 years as a Java developer. All our code was in CVS, then SVN, with Atlassian Fisheye providing a view into it.
When I left, Fisheye was reporting my personal, total LOC as +- 250,000. Here's the Fisheye description of its LOC metric, including the discussion on how each SVN user's personal LOC is calculated. Note the issues with branching and merging in SVN, and that LOC should usually only be based on TRUNK.