I asked this question about Microsoft .NET Libraries and the complexity of its source code. From what I'm reading, writing general purpose libraries and writing applications can be two different things. When writing libraries, you have to think about the client who could literally be everyone (supposing I release the library for use in the general public).
What kind of practices or theories or techniques are useful when learning to write libraries? Where do you learn to write code like the one in the .NET library? This looks like a "black art" which I don't know too much about.
That's a pretty subjective question, but here's on objective answer. The Framework Design Guidelines book (be sure to get the 2nd edition) is a very good book about how to write effective class libraries. The content is very good and the often dissenting annotations are thought-provoking. Every shop should have a copy of this book available.
You definitely need to watch Josh Bloch in his presentation How to Design a Good API & Why it Matters (1h 9m long). He is a Java guru but library design and object orientation are universal.
One piece of advice often ignored by library authors is to internalize costs. If something is hard to do, the library should do it. Too often I've seen the authors of a library push something hard onto the consumers of the API rather than solving it themselves. Instead, look for the hardest things and make sure the library does them or at least makes them very easy.
I will be paraphrasing from Effective C++ by Scott Meyers, which I have found to be the best advice I got:
Adhere to the principle of least astonishment: strive to provide classes whose operators and functions have a natural syntax and an intuitive semantics. Preserve consistency with the behavior of the built-in types: when in doubt, do as the ints do.
Recognize that anything somebody can do, they will do. They'll throw exceptions, they'll assign objects to themselves, they'll use objects before giving them values, they'll give objects values and never use them, they'll give them huge values, they'll give them tiny values, they'll give them null values. In general, if it will compile, somebody will do it. As a result, make your classes easy to use correctly and hard to use incorrectly. Accept that clients will make mistakes, and design your classes so you can prevent, detect, or correct such errors.
Strive for portable code. It's not much harder to write portable programs than to write unportable ones, and only rarely will the difference in performance be significant enough to justify unportable constructs.
Even programs designed for custom hardware often end up being ported, because stock hardware generally achieves an equivalent level of performance within a few years. Writing portable code allows you to switch platforms easily, to enlarge your client base, and to brag about supporting open systems. It also makes it easier to recover if you bet wrong in the operating system sweepstakes.
Design your code so that when changes are necessary, the impact is localized. Encapsulate as much as you can; make implementation details private.
Edit: I just noticed I very nearly duplicated what cherouvim had posted; sorry about that! But turns out we're linking to different speeches by Bloch, even if the subject is exactly the same. (cherouvim linked to a December 2005 talk, I to January 2007 one.) Well, I'll leave this answer here — you're probably best off by watching both and seeing how his message and way of presenting it has evolved :)
FWIW, I'd like to point to this Google Tech Talk by Joshua Bloch, who is a greatly respected guy in the Java world, and someone who has given speeches and written extensively on API design. (Oh, and designed some exceptionally good general purpose libraries, like the Java Collections Framework!)
Joshua Bloch, Google Tech Talks, January 24, 2007:
"How To Design A Good API and Why it
Matters" (the video is about 1 hour long)
You can also read many of the same ideas in his article Bumper-Sticker API Design (but I still recommend watching the presentation!)
(Seeing you come from the .NET side, I hope you don't let his Java background get in the way too much :-) This really is not Java-specific for the most part.)
Edit: Here's another 1½ minute bit of wisdom by Josh Bloch on why writing libraries is hard, and why it's still worth putting effort in it (economies of scale) — in a response to a question wondering, basically, "how hard can it be". (Part of a presentation about the Google Collections library, which is also totally worth watching, but more Java-centric.)
Krzysztof Cwalina's blog is a good starting place. His book, Framework Design Guidelines: Conventions, Idioms, and Patterns for Reusable .NET Libraries, is probably the definitive work for .NET library design best practices.
http://blogs.msdn.com/kcwalina/
The number one rule is to treat API design just like UI design: gather information about how your users really use your UI/API, what they find helpful and what gets in their way. Use that information to improve the design. Start with users who can put up with API churn and gradually stabilize the API as it matures.
I wrote a few notes about what I've learned about API design here: http://www.natpryce.com/articles/000732.html
I'd start looking more into design patterns. You'll probably not going to find much use for some of them, but as you get deeper into your library design the patterns will become more applicable. I'd also pick up a copy of NDepend - a great code measuring utility which may help you decouple things better. You can use .NET libraries as an example, but, personally, i don't find them to be great design examples mostly due to their complexities. Also, start looking at some open source projects to see how they're layered and structured.
A couple of separate points:
The .NET Framework isn't a class library. It's a Framework. It's a set of types meant to not only provide functionality, but to be extended by your own code. For instance, it does provide you with the Stream abstract class, and with concrete implementations like the NetworkStream class, but it also provides you the WebRequest class and the means to extend it, so that WebRequest.Create("myschema://host/more") can produce an instance of your own class deriving from WebRequest, which can have its own GetResponse method returning its own class derived from WebResponse, such that calling GetResponseStream will return your own class derived from Stream!
And your callers will not need to know this is going on behind the scenes!
A separate point is that for most developers, creating a reusable library is not, and should not be the goal. The goal should be to write the code necessary to meet requirements. In the process, reusable code may be found. In that case, it should be refactored out into a separate library, where it can be reused in the future.
I go further than that (when permitted). I will usually wait until I find two pieces of code that actually do the same thing, or which overlap. Presumably both pieces of code have passed all their unit tests. I will then factor out the common code into a separate class library and run all the unit tests again. Assuming that they still pass, I've begun the creation of some reusable code that works (since the unit tests still pass).
This is in contrast to a lesson I learned in school, when the result of an entire project was a beautiful reusable library - with no code to reuse it.
(Of course, I'm sure it would have worked if any code had used it...)
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I have been programming in object-oriented languages for years now but secretly I look at some of the things my colleagues do with envy. A lot of them seem to have some inner OO instinct that I don't have - no matter how hard I try. I've read all the good books on OO but still can't seem to crack it. I feel like the guy who gave 110% to be a professional footballer but just didn't have the natural talent to make it. I'm at a loss and thinking of switching careers - what should do I?
I would say focus less on the OO programming and focus more on the OO design. Grab a paper and a pencil (or maybe a UML modelling tool), and get away from the screen.
By practicing how to design a system, you'll start to get a natural feel for object relationships. Code is just a by-product of design. Draw diagrams and model your application in a purely non-code form. What are the relationships? How do your models interact? Don't even think about the code.
Once you've spent time designing... then translate it to code. You'll be surprised at just how quickly the code can be written from a good OO design.
After a lot of design practice, you'll start seeing common areas that can be modularized or abstracted out, and you'll see an improvement in both your designs and your code.
The easiest way is to learn concepts such as SOLID, DRY, FIT, DDD, TDD, MVC, etc. As you look up these acronyms it will lead you down many other rabbit holes and once you are done with your reading you should have a good understanding of what better object-oriented programming is!
SOLID podcasts: http://www.hanselminutes.com/default.aspx?showID=168, http://www.hanselminutes.com/default.aspx?showID=163
SOLID breakdown: http://butunclebob.com/ArticleS.UncleBob.PrinciplesOfOod
DRY: http://en.wikipedia.org/wiki/Don%27t_repeat_yourself
FIT: http://www.netwellness.org/question.cfm/38221.htm
DDD: http://dddcommunity.org/
DDD required reading: http://www.infoq.com/minibooks/domain-driven-design-quickly
TDD: http://en.wikipedia.org/wiki/Test-driven_development
MVC: http://en.wikipedia.org/wiki/Model%E2%80%93view%E2%80%93controller
And yes, rolling up your sleeves and coding is always a good idea. Make a small project to the best of your current abilities. Then read an article from above. Then refactor your code to meet the needs of what you just read. Repeat until you have refactored the hell out of your code. At the end you should not only know what OO is all about but you should be able to explain why it is important and how to get their the first time. Learning how to refactor is a key to good code too. What is right now is not right tomorrow.
Too many people think of coding first, objects, last.
You can read all the books you want but that's not going to teach you how to think in an object-oriented fashion--that takes practice and a certain methodology.
Here are a few methods that have
helped me: When you're away from
work and open-minded you can
practice by looking at everything as an object. Don't look at these
objects and wonder how you're going
to program them, look at them as
properties and functions only and
how they relate or inherit from each
other. For example, when you see a
person, they are an object and
therefore would represent a class.
They have properties like hair
color, skin tone, height, etc. They
do certain functions as well. They
walk, talk, sleep, etc. Some of the
functions these people do returns
results. For example, their working
function returns a dollar amount.
You can do this with everything you
see because everything is an object.
Bicycle, car, star, etc.
Before coding a project, design it by
using post-it notes and a dry-erase
board. This will make good practice
until you get the hang of this.
Think of your specific
object/function/property. Each of
those items will have its own
post-it note. Place them as a
hierarchy on the dry-erase board. In
this regard, function/properties
will be placed under the object. If
you have another object, do the same
for that one. Then ask yourself, do
any of these post it notes
(objects/functions/properties)
relate to each other. If two objects
use the same function, create a
parent object (post-it note) and put
it above the others with the
reusable function under the new
note. Draw a line using the
dry-erase marker from the two child
objects to the parent.
When all this is done, then worry
about the internals of how the class
works.
My suggestion would be to learn something different.
Learn functional programming, and apply what you learn from that to OOP. If you know C++, play around with generic programming.
Learn non-object-oriented languages.
Not just because you should use all these things as well (you should), or because they should completely replace OOP (they probably shouldn't), but because you can apply lessons from these to OOP as well.
The secret to OOP is that it doesn't always make sense to use it. Not everything is a class. Not every relationship or piece of behavior should be modeled as a class.
Blindly trying to apply OOP, or striving to write the best OOP code possible tends to lead to huge overengineered messes with far too many levels of abstraction and indirection and very little flexibility.
Don't try to write good OOP code. Try to write good code. And use OOP when it contributes to that goal.
In many fields there's a "eureka" moment where everything kind of comes together.
I remember feeling frustrated in high school geometry. I didn't know which theorem to apply on each step of the proof. But I kept at it. I learned each theorem in detail, and studied how they were applied in different example proofs. As I understood not only the definition of each theorem, but how to use it, I built up a "toolbox" of familiar techniques that I could pull out as needed.
I think it's the same in programming. That's why algorithms, data structures, and design patterns are studied and analyzed. It's not enough to read a book and get the abstract definition of a technique. You have to see it in action too.
So try reading more code, in addition to practicing writing it yourself. That's one beauty of open source, you can download lots of code to study. Not all of that code is good, but studying bad code can be just as educational as studying good code.
Learn a different language! Most developers using only Java (just as an example) have only a limited understanding of OO because they cannot separate language features and concepts. If you don't know it yet, have a look at python. If you know python, learn Ruby. Or choose one of the functional languages.
The aswer is in your question ;)
Practice, practice, practice.
Review your own code and learn from the mistakes.
TDD has helped me most in improving my overall skillset including OOP.
The more code you write, the more you will notice the pitfalls of certain programming practices. After enough time, and enough code, you will be able to identify the warning signs of these pitfalls and be able to avoid them. Sometimes when I write code, I will get this itch in the back of my mind telling me that there may be a better way to do this, even though it does what I need it to. One of my greatest programming weaknesses is "over-analyzing" things so much that it starts to dramatically slow down development time. I am trying to prevent these "itches" by spending a little more time on design, which usually results in a lot less time writing code.
...secretly I look at some of the things my colleagues do with envy. A lot of them seem to have some inner OO instinct that I don't have - no matter how hard I try...
I think you have answered your own question here. Reading good code is a good start, and understanding good code is even better, but understanding the steps to get to that good code is the best. When you see some code that you are envious of, perhaps you could ask the author how he/she arrived at that solution. This is entirely dependent on your work environment as well as the relationships with your colleagues. In any event, if anyone asks me the thought process behind any code I write, I don't hesitate to tell them because I know I would want them to do the same for me.
Language designers have interpreted "Object Oriented Programming" in different ways. For instance, see how Alan Kay, the man who first used the term OOP, defined it:
OOP to me means only messaging, local
retention and protection and hiding of
state-process, and extreme
late-binding of all things. It can be
done in Smalltalk and in LISP. There
are possibly other systems in which
this is possible, but I'm not aware of
them.
(Quoted from http://userpage.fu-berlin.de/~ram/pub/pub_jf47ht81Ht/doc_kay_oop_en).
It might seem strange that he don't consider Java and C++ OOP languages! But as the designer of one of the first and best OOP languages (Smalltalk) he has his own valid reasons for that. Why did Alan Kay consider Lisp an Object Oriented language but not Java? That question demands serious consideration by anyone who claims to understand OOP.
Erlang has an altogether different implemntation of OOP, Scheme has another.
It is worth considering all these alternative views. If possible learn all these languages! That will give you a broader outlook, put some new and powerful tools in your hand and make you a better programmer.
I have summarized my experiments with implementing an OOP language, based on ideas borrowed from Smalltalk, Scheme and Erlang in this article.
public void MasteryOfOOP()
{
while(true)
/* My suggestion is: */
DO: find a lot of well-written object oriented code and read it. Then
try to use the insights from it on your own coding. Then do it again. Then
have a colleague who is a good OOP look at it and comment. Maybe post a chunk
of your code on SO and ask for how it could be improved.
Then read some more of those books. Maybe they make a little more
sense now...?
Now go back to the top of this post, and do it again.
Repeat Forever.
}
}
If you're lost as to how to design object-oriented systems, start with the data. Figure out what stuff you need to keep track of and what information naturally goes together (for example, all of the specs of a model of car group together nicely).
Each of these kinds of thing you decide to track becomes a class.
Then when you need to be able to execute particular actions (for example, marking a model of car as decommissioned) or ask particular questions (for example, asking how many of a given model of car were sold in a given year), you load that functionality onto the class it interacts with most heavily.
In general, there should always be a pretty natural place for a given bit of code to live in your class structure. If there isn't, that signals that there's a place where the structure needs to be built out.
There's too much information about objects. The most important thing is to master the basics and everything falls into place more easily.
Here's a way to think about objects. Think about data structures in procedural languages. They are a group of fields without behaviour. Think about functions that receive pointers to those data structures and manipulate the latter. Now, instead of having them separate, define the functions inside the definition of the the structures and assume the functions usually receive a pointer to the data structure to manipulate. That pointer is called this. In sum, think about objects as the combination of status (data) and behaviour (methods - the fancy name for functions in OOP).
This is the absolute basic. There are three more concepts you must absolutely master:
Inheritance - This is all about code reuse.
Encapsulation - This is all about hiding the implementation from the interface. Simply put, everything ought to be private until proven otherwise.
Polymorphism - It doesn't matter the type of the reference variable, but the type of the actual instance to know which behaviour (method) is called. Java doesn't make it easy to have this concept very visible because by definition everything is polymorphic. .Net makes it easier to understand as you decide what is polymorphic and what is not, hence noticing the difference in behaviour. This is achieved by the combination of virtual and override.
If these concepts are very well understood, you'll be fine.
One last final tip: You mention the best books. Have you read "Thinking in Java" by Bruce Eckel? I recommend this book even to people who are beginning in .Net, as the OOP concepts are clearly laid out.
Become more agile, learn junit testing and study about Domain Driven Design. I suggest the book Domain-Driven Design: Tackling Complexity in the Heart of Software although it's a bit tough at some points.
OOP skills comes over time. Reading 1, 2 ...10 books doesn't cut it. Practice writing some code. If you are working in a programming enviornment...that can be helpful. If not try getting into one. Offer to develop some application(s) for free. You have to get your hands dirty. Remember...no application is perfect from the ground up.That's why there is re-factoring.
Also...don't get carried away with the OOP too much...it somes over time. Worry about developing fully functional applications.
Try some programming in Self, one of the most pure OO languages around. So pure, in fact, that it doesn't even have classes, only objects. It also doesn't have variables, fields, statics, attributes, only methods. Also interesting is the fact that every object in the system is also an object on the screen and vice-versa.
Some of the interesting papers on Self are Prototype-Based Application Construction Using SELF 4.0 (the Self tutorial), Self: The Power of Simplicity and Organizing Programs Without Classes. Also, Self: The Video (Randall B. Smith; Dave Ungar) is terrific, having two of the language's designers explain Self's ideas.
This works for pretty much any concept, actually, at least for me: find the language which most purely embodies the concept you want to learn about and just use it.
OO finally clicked for me after I tried to program a bank-like program that handled transactions, calculated interest, and kept track of it all. I did it while I was learning Java. I would suggest just trying it, completing it, and then when you're done go look at a GOOD solution and see what you could've done better.
I also think OOP skills strenghten mostly with practice. Consider changing your company, if you've been there for more than 3 years. Certainly, this is not valid for all jobs, but often a man gets used to the projects and practices at a company and stops advancing as time passes.
Roll up your sleeves and code!
You said the answer yourself: practice. Best solution for this is to develop a game. Use the concepts you learnt in the books there.
Have you read the chapter on OO from the first edition of Scott Meyers "Effective C++" book? It didn't make it to later editions, but it was a great explanation. The title was basically "say what you mean, mean what you say" about suitable conventions.
Actually, you might like to see my answer to a similar question over here.
HTH
cheers,
OOP is not a thing you can master by reading thousands of books. Rather you have to feel the inner concepts. Read anything but try to feel what you read. Build a concept in the back of your mind and try to match those concepts when you face a new scenario. Verify and Update your concepts as you explore new things.
Good luck!
Plan things out. Ask yourself how you want your objects to relate to eachother and seek out how things can be changed and modularized.
Code things in such a way that if you wanted to change 1 piece of the code, you only have to change that 1 piece of code and not 50 instances of it.
beer helps. seriously. lie out on a couch with an A3 sized scribble pad, a pen and a beer. Lock the dog, cat and wife outside. And think about the problem while relaxed. Don't even dare draw an API on it!
Flowcharts, Responsibity cards (CRC) and beer (but not too much) go a long way.
Easiest way to refactor code is to not have to in the first place.
http://misko.hevery.com/code-reviewers-guide/
Those small simple rules will make you a better OO programmer. Follow the rules religiously as you code and you will find your code is better than it would otherwise be.
You'll also want to learn the Solid Principles: http://butunclebob.com/ArticleS.UncleBob.PrinciplesOfOod
As much as these principles and ways of programming cause debate, they are the only way to truly write excellent code.
You may already write code this way and not know it-- if so, great. But if you need a goal to strive towards, these are the gold standard.
Give up! Why do you need that that OOP? Just write some usable app. Doesnt metter using OOP, procedual or functional approach.
Whataver approach you choose Python language should be sutable to practice it.
You're my target audience. Look at Building Skills in OO Design
Perhaps this can help.
I have an Access db I use for my checkbook (with a good amount of fairly simple VBA behind it) and I'd like to rewrite it as a stand-alone program with a SQL backend. I'm thinking of using either C++, Java, or Python. I had assumed, before I started, that I would write it OO because I thought that I would think "in OO terms" (due to a OO Logic class and a C++ class I took), but I'm finding that I can only visualize it as procedural (but maybe because I'm mentally stuck in thinking of how the db works in Access). How do I decide? Am I making sense or does it seem like I'm not understanding the concepts?
Thanks for your help.
I'd suggest OO - it's not harder than procedural programming, actually easier to maintain with the right tool. Delphi would be my choice - great DB programming support, visual designer, strongly-typed, plenty of components available. There are many great applications that are written in Delphi. Often underestimated, there are many reasons it's got a loyal following.
Now I'll duck as the Delphi-haters load up with tomatoes.
Well, OO may well be overkill, but it is excellent practice. Any code monkey can write procedural code. Its the path of least resistance in every case, which is why most people use it for one off apps that don't do much. However, if you're writing to get experience in working with OO, than it is best to think of it that way. You could start by designing an object that manages financial transaction, then you will also need a way to interact with the DB. Perhaps you could write a DB layer where you abstract away the database calls from the transaction object using the Entity framework where you could learn LINQ (or whatever the JAVA equivalent is). This is all assuming that you are doing this for fun and practice.
oo seems to be overkill for a simple checkbook app. Try something on a larger scale like something to manage all your financial accounts. This way designing an account class would make sense
Well it depends on your motivation. If you want a checkbook application as quickly as possible, just churn out the procedural code. No-one other than you will know the difference. If you want to use this application to better yourself as aprogrammer. Take the time to learn how to write in in OO.
I'd go with Python: no compiling and uses dynamic typing (you can use strict typing too if you want). Plus, it has a huge following in the open source community which means great support, tools, and documentation for free.
As for OO vs. Procedural -- all these languages you've mentioned could be written in a procedural style -- that is, one big class/method that does everything -- but you'll soon find that you'll want to follow DRY principles (Don't Repeat Yourself) and start with some private methods that do one particular thing well. From then, you'll want to group similar things into separate classes, and then from there you'll want to abstract those classes... see where I'm going here?
In my opinion you should concentrate less on the OO versus procedural thing. If you have the possibility to go procedural in the beginning, then go procedural. It's the easiest thing you can do to get you started. The OO thing, on the other hand, may just as well qualify as YAGNI (You Ain't Gonna Need It).
What you should do though, is to write tests, unit tests and then integration tests. And you should strive to write tests first. This way, even if you begin with a procedural application you may later on refactor it into a full-fledged OO application. But, only if you need objects. These tests will be you're safety net when moving around code in your application.
Trying to think your applications into object from the beginning may lead you to an point where you're stuck with your class hierarchies and architecture.
I'm not a genius, so I may be wrong, but in my experience, starting with simple functions and then thinking about grouping them into objects or modules is better than starting by saying: OK, I'll have this object that interacts with this object, which is implementing pattern X, so this way I'll decouple interface Y from implementation Z. Later on, you may observe that your domain model is weak. Take an evolutionary design path and start with small building blocks.
If you are looking for a quick app that you can extend, check out Dynamic Data.
Lately, I've been making use a lot of the Strategy Pattern along with the Factory Pattern. And I really mean a lot. I have a lot of "algorithms" for everything and factories that retrieve algorithms based on parameters.
Even though the code seems very extensible, and it is, having N factories seems a bit of an abuse.
I know this is pretty subjective, and we're talking without seeing code, but is this acceptable in real world code? Would you change something ?
OK- ask yourself a question. does/will this algorithm implementation ever change? If no then remove the strategy.
I am maintence.
I once was forced (by my pattern lovin' boss) to write a set of 16 "buffer interpreter tuxedo services" using an AbstractFactory and a double DAO pattern in C++ (no reflections, no code gen). All up it something like 20,000 lines of the nastiest code I've even seen (not the least because I didn't really know C++ when I started) and it took about three months.
Since my old boss has moved on I've rewritten them using good 'ole "straight up and down" procedural style C++, with couple of funky-macros... each service is like 60 lines of code, times 16... all up less than a 1000 lines of really SIMPLE code; so simple that even I can follow it.
Cheers. Keith.
Whenever I'm implementing code in this fashion, some questions I ask are:
what components do I need to substitute to test ?
what components will I expect users/admins to disable or substitute (e.g. via Spring configs or similar) ?
what components do I expect or suspect will not be required in the future due to (possibly) changing requirements ?
This all drives how I construct object or components (via factories) and how I implement algorithms. The above is vague, but (of course) the requirements can be similarly difficult to pin down. Without seeing your implementation and your requirements, I can't comment further, but the above should act as some guideline to help you determine whether what you've done is overkill.
If you're using the same design pattern all over the place, perhaps you should either switch to a language that has better support for what you're trying to do or rethink your code to be more idiomatic in your language of choice. After all, that's why we have more than one programming language.
Would depends on the kind of software I'm working on.
Maintenance asks for simple code and factories is NOT simple code.
But extensibility asks sometimes for factories...
So you have to take both in consideration.
Just have in mind that most of the time, you will have to maintain a source file MANY times a year and you will NOT have to extend it.
IMO, patterns should only be used when absolutely needed. If you think it can be handy in two years, you are better to use them... in two years.
How complex is the work the factory is handling? Does object creation really need to be abstracted to a different class? A variation of the factory method is having a simple, in-class factory. This really works best if any dependencies have already been injected.
For instance,
public class Customer
{
public Customer CreateNewCustomer()
{
// handle minimally complex create logic here
}
}
As far as Strategy overuse... Again, as #RichardOD explained, will the algorithm ever really change?
Always keep in mind the YAGNI principle. You Aren't Gonna Need It.
Can't you make an AbstractFactory instead off different standalone factories?
AlgorithmFactory creates the algorithms you need based on the concrete factory.
[Edit:] Earlier I asked this as a perhaps poorly-framed question about when to use OOP versus when to use procedural programming - some responses implied I was asking for help understanding OOP. On the contrary, I have used OOP a lot but want to know when to use a procedural approach. Judging by the responses, I take it that there is a fairly strong consensus that OOP is usually a better all-round approach but that a procedural language should be used if the OOP architecture will not provide any reuse benefits in the long term.
However my experience as a Java programmer has been otherwise. I saw a massive Java program that I architected rewritten by a Perl guru in 1/10 of the code that I had written and seemingly just as robust as my model of OOP perfection. My architecture saw a significant amount of reuse and yet a more concise procedural approach had produced a superior solution.
So, at the risk of repeating myself, I'm wondering in what situations should I choose a procedural over an object-oriented approach. How would you identify in advance a situation in which an OOP architecture is likely to be overkill and a procedural approach more concise and efficient.
Can anyone suggest examples of what those scenarios would look like?
What is a good way to identify in advance a project that would be better served by a procedural programming approach?
I like Glass' rules of 3 when it comes to Reuse (which seems to be what you're interested in).
1) It is 3 times as difficult to
build reusable components as single
use components 2) A reusable
component should be tried out in three
different applications before it will
be sufficiently general to accept into
a reuse library
From this I think you can extrapolate these corollaries
a) If you don't have the budget
for 3 times the time it would take you
to build a single use component, maybe
you should hold off on reuse. (Assuming Difficulty = Time)
b) If
you don't have 3 places where you'd
use the component you're building,
maybe you should hold off on building
the reusable component.
I still think OOP is useful for building the single use component, because you can always refactor it into something that is really reusable later on. (You can also refactor from PP to OOP but I think OOP comes with enough benefits regarding organization and encapsulation to start there)
Reusability (or lack of it) is not bound to any specific programming paradigm. Use object oriented, procedural, functional or any other programming as needed. Organization and reusability come from what you do, not from the tool.
Those who religiously support OOP don't have any facts to justify their support, as we see here in these comments as well. They are trained (or brain washed) in universities to use and praise OOP and OOP only and that is why they support it so blindly. Have they done any real work in PP at all? Other then protecting code from careless programmers in a team environment, OOP doesn't offer much. Personally working both in PP and OOP for years, I find that PP is simple, straight forward and more efficient, and I agree with the following wise men and women:
(Reference: http://en.wikipedia.org/wiki/Object-oriented_programming):
A number of well-known researchers and programmers have criticized OOP. Here is an incomplete list:
Luca Cardelli wrote a paper titled “Bad Engineering Properties of Object-Oriented Languages”.
Richard Stallman wrote in 1995, “Adding OOP to Emacs is not clearly an improvement; I used OOP when working on the Lisp Machine window systems, and I disagree with the usual view that it is a superior way to program.”
A study by Potok et al. has shown no significant difference in productivity between OOP and procedural approaches.
Christopher J. Date stated that critical comparison of OOP to other technologies, relational in particular, is difficult because of lack of an agreed-upon and rigorous definition of OOP. A theoretical foundation on OOP is proposed which uses OOP as a kind of customizable type system to support RDBMS.
Alexander Stepanov suggested that OOP provides a mathematically-limited viewpoint and called it “almost as much of a hoax as Artificial Intelligence” (possibly referring to the Artificial Intelligence projects and marketing of the 1980s that are sometimes viewed as overzealous in retrospect).
Paul Graham has suggested that the purpose of OOP is to act as a “herding mechanism” which keeps mediocre programmers in mediocre organizations from “doing too much damage”. This is at the expense of slowing down productive programmers who know how to use more powerful and more compact techniques.
Joe Armstrong, the principal inventor of Erlang, is quoted as saying “The problem with object-oriented languages is they’ve got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle.”
Richard Mansfield, author and former editor of COMPUTE! magazine, states that “like countless other intellectual fads over the years (“relevance”, communism, “modernism”, and so on—history is littered with them), OOP will be with us until eventually reality asserts itself. But considering how OOP currently pervades both universities and workplaces, OOP may well prove to be a durable delusion. Entire generations of indoctrinated programmers continue to march out of the academy, committed to OOP and nothing but OOP for the rest of their lives.” and also is quoted as saying “OOP is to writing a program, what going through airport security is to flying”.
You gave the answer yourself - big projects simply need OOP to prevent getting too messy.
From my point of view, the biggest advantage of OOP is code organization. This includes the principles of DRY and encapsulation.
I would suggest using the most concise, standards-based approach that you can find for any given problem. Your colleague who used Perl demonstrated that a good developer who knows a particular tool well can achieve great results regardless of the methodology. Rather than compare your Java-versus-Perl projects as a good example of the procedural-versus-OOP debate, I would like to see a face-off between Perl and a similarly concise language such as Ruby, which happens to also have the benefits of object orientation. Now that's something I'd like to see. My guess is Ruby would come out on top but I'm not interested in provoking a language flame-war here - my point is only that you choose the appropriate tool for the job - whatever approach can accomplish the task in the most efficient and robust way possible. Java may be robust because of its object orientation but as you and your colleague and many others who are converting to dynamic languages such as Ruby and Python are finding these days, there are much more efficient solutions out there, whether procedural or OOP.
I think DRY principle (Don't Repeat Yourself) combined with a little Agile is a good approach. Build your program incrementally starting with the simplest thing that works then add features one by one and re-factor your code as necessary as you go along.
If you find yourself writing the same few lines of code again and again - maybe with different data - it's time to think about abstractions that can help separate the stuff that changes from the stuff that stays the same.
Create thorough unit tests for each iteration so that you can re-factor with confidence.
It's a mistake to spend too much time trying to anticipate which parts of your code need to be reusable. It will soon become apparent once the system starts to grow in size.
For larger projects with multiple concurrent development teams you need to have some kind of architectural plan to guide the development, but if you are working on your own or in small cooperative team then the architecture will emerge naturally if you stick to the DRY principle.
Another advantage of this approach is that whatever you do is based on real world experience. My favourite analogy - you have to play with the bricks before you can imagine how the building might be constructed.
I think you should use procedural style when you have a very well specified problem, the specification won't change and you want a very fast running program for it. In this case you may trade the maintainability for performance.
Usually this is the case when you write a game engine or a scientific simulation program. If your program calculate something more than million times per second it should be optimized to the edge.
You can use very efficient algorithms but it won't be fast enough until you optimize the cache usage. It can be a big performance boost your data is cached. This means the CPU don't need fetch bytes from the RAM, it know them. To achieve this you should try to store your data close to each other, your executable and data size should be minimal, and try using as less pointers as you can (use static global fixed sized arrays where you can afford).
If you use pointers you are continuously jumping in the memory and your CPU need to reload the cache every time. OOP code is full of pointers: every object is stored by its memory address. You call new everywhere which spread your objects all over the memory making the cache optimization almost impossible (unless you have an allocator or a garbage collector that keeps things close to each other). You call callbacks and virtual functions. The compiler usually can't inline the virtual functions and a virtual function call is relatively slow (jump to the VMT, get the address of the virtual function, call it [this involves pushing the parameters and local variables on the stack, executing the function then popping everything]). This matters a lot when you have a loop running from 0 to 1000000 25 times in every second. By using procedural style there aren't virtual function and the optimizar can inline everything in those hot loops.
If the project is so small that it would be contained within one class and is not going to be used for very long, I would consider using functions. Alternatively if the language you are using does not support OO (e.g. c).
"The problem with object-oriented languages is they’ve got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle.” —Joe Armstrong
Do you want the jungle?
I think the suitability of OOP depends more on the subject area you're working in than the size of the project. There are some subject areas (CAD, simulation modeling, etc.) where OOP maps naturally to the concepts involved. However, there are a lot of other domains where the mapping ends up being clumsy and incongruous. Many people using OOP for everything seem to spend a lot of time trying to pound square pegs into round holes.
OOP has it's place, but so do procedural programming, functional programming, etc. Look at the problem you're trying to solve, then choose a programming paradigm that allows you to write the simplest possible program to solve it.
Procedural programs can be simpler for a certain type of program. Typically, these are the short script-like programs.
Consider this scenario:
Your code is not OO. You have data structures and many functions throughout your progam that operate on the data structures. Each function takes a data structure as a parameter and does different things depending on a "data_type" field in the data structure.
IF all is working and not going to be changed, who cares if it's OO or not? It's working. It's done. If you can get to that point faster writing procedurally, then maybe that's the way to go.
But are you sure it's not going to be changed? Let's say you're likely to add new types of data structures. Each time you add a new data structure type that you want those functions to operate on, you have to make sure you find and modify every one of those functions to add a new "else if" case to check for and add the behavior you want to affect the new type of data structure. The pain of this increases as the program gets larger and more complicated. The more likely this is, the better off you would be going with the OO approach.
And - are you sure that it's working with no bugs? More involved switching logic creates more complexity in testing each unit of code. With polymorphic method calls, the language handles the switching logic for you and each method can be simpler and more straightforward to test.
The two concepts are not mutually exclusive, it is very likely that you will use PP in conjunction with OOP, I can't see how to segregate them.
I believe Grady Booch said once that you really start to benefit a lot from OOP at 10000+ lines of code.
However, I'd always go the OO-way. Even for 200 lines. It's a superior approach in a long term, and the overhead is just an overrated excuse. All the big things start small.
One of the goals of OOP was to make reusability easier however it is not the only purpose. The key to learning to use objects effectively is Design Patterns.
We are all used to the idea of algorithms which tell us how to combine different procedures and data structures to perform common tasks. Conversely look at Design Patterns by the Gang of Four for ideas on how to combine objects to perform common tasks.
Before I learned about Design Patterns I was pretty much in the dark about how to use objects effectively other than as a super type structure.
Remember that implementing Interfaces is just as important if not more important than inheritance. Back in the day C++ was leading example of object oriented programming and using interfaces are obscured compared to inheritance (virtual functions, etc). The C++ Legacy meant a lot more emphasis was placed on reusing behavior in the various tutorials and broad overviews. Since then Java, C#, and other languages have moved interface up to more a focus.
What interfaces are great for is precisely defining how two object interact with each. It is not about reusing behavior. As it turns out much of our software is about how the different parts interact. So using interface gives a lot more productivity gain than trying to make reusable components.
Remember that like many other programming ideas Objects are a tool. You will have to use your best judgment as to how well they work for your project. For my CAD/CAM software for metal cutting machines there are important math functions that are not placed in objects because there is no reason for them be in objects. Instead they are exposed from library and used by the object that need them. Then there is are some math function that were made object oriented as their structure naturally lead to this setup. (Taking a list of points and transforming it in on of several different types of cutting paths). Again use your best judgment.
Part of your answer depends on what language you're using. I know that in Python, it's pretty simple to move procedural code into a class, or a more formal object.
One of my heuristics is a based on how the "state" of the situation is. If the procedure pollutes the namespace, or could possibly affect the global state (in a bad, or unpredictable way), then encapsulating that function in an object or class is probably wise.
My two cents...
Advantages of procedural programming
Simple designing (fast proof of concept, battle with dramatically
dynamic requirements)
Simple inter-project communications
Natural when temporal order matters
Less overhead at runtime
The more Procedural code become good the closer it's to Functional. And advantages of FP are well known.
I always begin designing in a top-down fashion and in the top parts it's much easier to think in OOP terms. But when comes the time to code some little specific parts you are much more productive with just procedure programming.
OOP is cool in designing and in shaping the project, so that the divide-et-impera paradigm can be applied. But you cannot apply it in every aspect of your code, as it were a religion :)
If you "think OO" when you're programming, then I'm not sure it makes sense to ask "when should I revert to procedural programming?" This is equivalent to asking java programmers what they can't do as well because java requires classes. (Ditto .NET languages).
If you have to make an effort to get past thinking procedurally, then I'd advise asking about how you can overcome that (if you care to); otherwise stay with procedural. If it's that much effort to get into OOP-mode, your OOP code probably won't work very well anyway (until you get further along the learning curve.)
IMHO, the long term benefits of OOP outweigh the time saved in the short term.
Like AZ said, using OOP in a procedural fashion (which I do quite a bit), is a good way to go (for smaller projects). The bigger the project, the more OOP you should employ.
You can write bad software in both concepts. Still, complex software are much easier to write, understand and maintain in OO languages than in procedural. I wrote highly complex ERP applications in procedural language (Oracle PL/SQL) and then switched to OOP (C#). It was and still is a breath of fresh air.
To this point, the arguments of using OO for DRY and encapsulation is just adding unnecessary complexity in terms of how implicit it is and just sheer of how many layers that a class can inherit a lot of properties and methods into it.
not to mention that it's really hard to design a good OO cause you'd end up adding unrelated/unnecessary things that are going to be inherited throughout the whole layers of classes that inherits them. which is really bad if one parent class gets messy, the whole codebase is messy. and gets refactored.
also the fact that those inherited properties are not specifically fit into the use case to the class that inherits it which requires to be overridden. and to the ones that don't need them at all just have them for no good reason.
for something that does not need to be shared, sure there's abstract properties. but you'd end up having to implement them in all the instances that tries to inherits them.
this inheritance is just too magicky and gets dangerous.
but I'd give OO credit on how it's good at enforcing of what should be available. but then again it's too much power that is really easy to be wrongly used.
In my opinion, final class should be the default. and you need to deliberately choose if you want to allow it to inheritance.
Most studies have found that OO code is more concise than procedural code. If you look at projects that re-wrote existing C code in C++ (not something I necessarily advise, BTW) , you normally see reductions in code size of between 50 and 75 percent.
So the answer is - always use OO!
I've been studying OOP for quite a while now and I have a good grasp of the theory. I read the Head First book on OOP and, while it reinforced a lot of the theory, I found the case studies to be somewhat trivial.
I find that I'm applying OOP principles to my code each day, but I'm not sure if I'm applying them correctly. I need to get to the point where I am able to look at my code and know whether I'm using inheritance appropriately, whether my object is cohesive enough, etc.
Does anyone have any good recommendations (books, online guides, blogs, walk-throughs, etc.) for taking the next step in developing solid OOP skills?
I am working primarily in .NET (visual basic), but I welcome suggestions that incorporate various platforms.
Read Refactoring by Martin Fowler, and apply it to your own work.
It will take you through a litany of malodorous characteristics of software code that describe how to detect improperly constructed classes, and even more importantly, how to fix them.
Consider looking into Design Patterns. Although it seems like they aren't commonly used in enterprise applications (I've seen them more commonly used in API's and Frameworks than embedded into enterprise code), they could be applied to make software simpler or more robust in a lot of situations if only developers knew how to apply them.
The key is to understand the design patterns first, then with experience you'll learn how to apply them.
There is a Head First book on design patterns that teaches the concept pretty simply, although if you want a book that really covers design patterns in detail, check out the Gang of Four design patterns book, which is basically what made design patterns mainstream and is referred to almost every time the topic is brought up.
Design patterns can be applied in pretty much any object-oriented language to some degree or another, although some patterns can be overkill or over engineering in some cases.
EDIT:
I also want to add, you should check out the book Code Complete 2. It's a very influential book in the world of software development. It covers a lot of different concepts and theories. I learn something new every time I read it. It's such a good book that if I read it every 6 months to a year, I look at it from a different perspective that makes me a better programmer just by re-reading it. No matter how much you might think you know, this book will make you realize just how little you really know. It's really a great book. I can't stress how much you should own this book.
If you already have the basics, I believe only experience will get you further. You say you are not sure if you are applying the principles correctly, but there is no one correct way. Code you write today, you'll look at in 6 months time, and wonder why you wrote it that way, and probably know of a better, cleaner way of doing it. I also guarantee that after 10 years, you'll still be learning new techniques and tricks. Don't worry too much about it, it will come, just read as much as you can, and try and apply what you read in small chunks.
I am currently half-way through the following book:
http://www.amazon.com/Applying-UML-Patterns-Introduction-Object-Oriented/dp/0131489062
I cannot recommend this book strongly enough in terms of learning a real-life, professional-grade, practical approach to drafting and applying a well-formed and iterative design strategy before diving into code.
I, too, read the "Head First" book and felt that I was much better off for having read it.
After having a few years of working-world experience, I now view the Craig Larman book that I am recommending to be a perfect "next step" for me.
About the Presence of "UML" in this Book Title:
Whether you have positive feelings or negative feelings about UML notation, please do not let that influence your decision to buy the book (ISBN 0131489062) in either direction.
The prominence of "UML" in the title is misleading. While the author does use and explain UML notation, these explanations are extremely well-woven into relevant design discussions, and at no time does this book read like a boring UML spec.
In fact, here is a quote taken directly from the book:
What's important is knowing how to think and design in objects, which is a very different and much more valuable skill than knowing UML notation. While drawing a diagram, we need to answer key questions: What are the responsibilities of the object? Who does it collaborate with? What design patterns should be applied? Far more important than knowing the difference between UML 1.4 and 2.0 !
This book at times seems like it is "speaking to" a lead architect or a project manager. What I mean to say by that is that it assumes that the reader has significant control over the planning and direction of a software project.
Nonetheless, even if you are only responsible for some very small piece of your company's projects and products, I would still recommend this book and encourage you to apply some "scaled down" modifications of the book's advice to your piece of the project.
My OOP epiphany came from Grady Booch's book, way long time ago. Suddenly I realized why objects were good.
While polymorphism is cool, encapsulation is 75% of why objects are cool. It is sort of like an interface: you see the buttons but not the wiring. Before objects, only the most disciplined coders kept their grubby fingers off the internal bits of other people's procedures (it was called "structured programming").
Object make it easy to Do the Right Thing. Inheritance and polymorphism are little bonuses.
One way to learn about objects is to read other peoples' code. I learned a lot by reading the source code for the Delphi VCL framework. Even just looking at the documentation for Java will help you see what a single object class should do and how it is designed to be used by other objects.
Start a project of your own and pay attention when you want to sub-class your own classes and find that you have to go back and break up some protected methods so you can override just one piece of a process instead of replacing all of it. See how ancestors talk to descendants by calling abstract functions. In other words, go make a lot of mistakes and learn from them.
Enjoy!
Frankly, re-reading old David Parnas papers on information hiding helps me get in the right state of mind. The case studies may not be directly applicable but you should be able to get some useful generalizations out of them.
My epiphany happened when I tried to implement a very OO problem (dynamically and recursively building SQL statements) in VB6. The best way to understand polymorphism or inheritance is to need it and not be able to use it.
One thing that will definitely help you is working on a well-known, respected open source project. Either dig through the source code and see how things are done or try to make some additions / modifications. You'll find that there isn't one style or one right answer for most problems, but by looking at several projects, you'll be able to get a wide view of how things can be done. From there, you'll begin to develop your own style and will hopefully make some contributions to open source in the process.
I think you have to attempt and fail at implementing OO solutions. That's how I did it anyway. What I mean by fail is that you end up writing smelly code while successfully delivering a working solution. After it's written you'll get a feel for where things didn't quite feel right. You may have some epiphanies, and/or you may go and hunt for a slicker solution from other programmers. Undoubtedly you'll implement some variation of standard design patterns by accident. In hindsight, a light will click on (oh! so that's what a visitor is for), and then understanding will accelerate.
As others have said, I think tooling through some good OO open source code is a good idea. So is working with more experienced programmers who would be willing to critique your work. However understanding comes through doing.
You might want to try to read (and write) some Smalltalk for a while. Squeak is a free implementation that can show you the power of a fully object-oriented environment (unlike java or .net). All library code source is included. The language itself is incredibly simple. You'll find that java and c# are slowly adding the features well-known to Smalltalk since 1980.
Tortoise HG is extrodanarily well designed piece of OO open source software (written in Python).
If you already understand the basics, building something from scratch in a fully object oriented language will be a good step in fully understanding OOP software architecture. If you don't know Python, Python Essential Reference will take you through the language in full in a few days to a week.
After you understand the language take a look through the software above and you'll have all sorts of epiphanies.
To understand basically anything thoroughly, you need to have a decent knowledge of at least one abstraction level above and one level below it. In the case of OO, others have mentioned design patterns as the layer above OO. This helps a lot to illustrate why OO is useful.
As far as the layer below OO, try to play around with higher-order functions/late binding for a while and get a feel for how these relatively simple constructs are used. Also, try to understand how OO is implemented under the hood (vtables, etc.) and how it can be done in pure C. Once you grok the value of using higher order functions and late binding, you'll quickly realize that OO is just a convenient syntax for passing around a set of related functions and the data they operate on.