What is the term for improving an object/class model? - oop

How do you call it when your buddy designs a class Dinosaur, that represents at the same time prehistoric dinosaurs (animals), contemporary robotic dinosaurs (toys) and US laws regarding keeping such animals and/or robots, and you come and break it down into classes DinosaurProper, DinosaurRobot, ExoticPetKeepingInUS and RobotOwnershipInUS? What is the smartass catchphrase or catchword for this?

Refactoring aimed at satisfying the Single Responsibility Principle (SRP).

Depdning on the exact structure of the initial design it may be sometimes called
ReplaceTypeCodeWithSubclasses or ExtractSubclass

Related

Practical uses of OOP

I recently had a debate with a colleague who is not a fan of OOP. What took my attention was what he said:
"What's the point of doing my coding in objects? If it's reuse then I can just create a library and call whatever functions I need for whatever task is at hand. Do I need these concepts of polymorphism, inheritance, interfaces, patterns or whatever?"
We are in a small company developing small projects for e-commerce sites and real estate.
How can I take advantage of OOP in an "everyday, real-world" setup? Or was OOP really meant to solve complex problems and not intended for "everyday" development?
My personally view: context
When you program in OOP you have a greater awareness of the context. It helps you to organize the code in such a way that it is easier to understand because the real world is also object oriented.
The good things about OOP come from tying a set of data to a set of behaviors.
So, if you need to do many related operations on a related set of data, you can write many functions that operate on a struct, or you can use an object.
Objects give you some code reuse help in the form of inheritance.
IME, it is easier to work with an object with a known set of attributes and methods that it is to keep a set of complex structs and the functions that operate on them.
Some people will go on about inheritance and polymorphism. These are valuable, but the real value in OOP (in my opinion) comes from the nice way it encapsulates and associates data with behaviors.
Should you use OOP on your projects? That depends on how well your language supports OOP. That depends on the types of problems you need to solve.
But, if you are doing small websites, you are still talking about enough complexity that I would use OOP design given proper support in the development language.
More than getting something to just work - your friend's point, a well designed OO design is easier to understand, to follow, to expand, to extend and to implement. It is so much easier for example to delegate work that categorically are similar or to hold data that should stay together (yes even a C struct is an object).
Well, I'm sure a lot of people will give a lot more academically correctly answers, but here's my take on a few of the most valuable advantages:
OOP allows for better encapsulation
OOP allows the programmer to think in more logical terms, making software projects easier to design and understand (if well designed)
OOP is a time saver. For example, look at the things you can do with a C++ string object, vectors, etc. All that functionality (and much more) comes for "free." Now, those are really features of the class libraries and not OOP itself, but almost all OOP implementations come with nice class libraries. Can you implement all that stuff in C (or most of it)? Sure. But why write it yourself?
Look at the use of Design Patterns and you'll see the utility of OOP. It's not just about encapsulation and reuse, but extensibility and maintainability. It's the interfaces that make things powerful.
A few examples:
Implementing a stream (decorator pattern) without objects is difficult
Adding a new operation to an existing system such as a new encryption type (strategy pattern) can be difficult without objects.
Look at the way PostgresQL is
implemented versus the way your
database book says a database should
be implemented and you'll see a big
difference. The book will suggest
node objects for each operator.
Postgres uses myriad tables and
macros to try to emulate these nodes.
It is much less pretty and much
harder to extend because of that.
The list goes on.
The power of most programming languages is in the abstractions that they make available. Object Oriented programming provides a very powerful system of abstractions in the way it allows you to manage relationships between related ideas or actions.
Consider the task of calculating areas for an arbitrary and expanding collection of shapes. Any programmer can quickly write functions for the area of a circle, square, triangle, ect. and store them in a library. The difficulty comes when trying to write a program that identifies and calculates the area of an arbitrary shape. Each time you add a new kind of shape, say a pentagon, you would need to update and extend something like an IF or CASE structure to allow your program to identify the new shape and call the correct area routine from your "library of functions". After a while, the maintenance costs associated with this approach begin to pile up.
With object-oriented programming, a lot of this comes free-- just define a Shape class that contains an area method. Then it doesn't really matter what specific shape you're dealing with at run time, just make each geometrical figure an object that inherits from Shape and call the area method. The Object Oriented paradigm handles the details of whether at this moment in time, with this user input, do we need to calculate the area of a circle, triangle, square, pentagon or the ellipse option that was just added half a minute ago.
What if you decided to change the interface behind the way the area function was called? With Object Oriented programming you would just update the Shape class and the changes automagically propagate to all entities that inherit from that class. With a non Object Oriented system you would be facing the task of slogging through your "library of functions" and updating each individual interface.
In summary, Object Oriented programming provides a powerful form of abstraction that can save you time and effort by eliminating repetition in your code and streamlining extensions and maintenance.
Around 1994 I was trying to make sense of OOP and C++ at the same time, and found myself frustrated, even though I could understand in principle what the value of OOP was. I was so used to being able to mess with the state of any part of the application from other languages (mostly Basic, Assembly, and Pascal-family languages) that it seemed like I was giving up productivity in favor of some academic abstraction. Unfortunately, my first few encounters with OO frameworks like MFC made it easier to hack, but didn't necessarily provide much in the way of enlightenment.
It was only through a combination of persistence, exposure to alternate (non-C++) ways of dealing with objects, and careful analysis of OO code that both 1) worked and 2) read more coherently and intuitively than the equivalent procedural code that I started to really get it. And 15 years later, I'm regularly surprised at new (to me) discoveries of clever, yet impressively simple OO solutions that I can't imagine doing as neatly in a procedural approach.
I've been going through the same set of struggles trying to make sense of the functional programming paradigm over the last couple of years. To paraphrase Paul Graham, when you're looking down the power continuum, you see everything that's missing. When you're looking up the power continuum, you don't see the power, you just see weirdness.
I think, in order to commit to doing something a different way, you have to 1) see someone obviously being more productive with more powerful constructs and 2) suspend disbelief when you find yourself hitting a wall. It probably helps to have a mentor who is at least a tiny bit further along in their understanding of the new paradigm, too.
Barring the gumption required to suspend disbelief, if you want someone to quickly grok the value of an OO model, I think you could do a lot worse than to ask someone to spend a week with the Pragmatic Programmers book on Rails. It unfortunately does leave out a lot of the details of how the magic works, but it's a pretty good introduction to the power of a system of OO abstractions. If, after working through that book, your colleague still doesn't see the value of OO for some reason, he/she may be a hopeless case. But if they're willing to spend a little time working with an approach that has a strongly opinionated OO design that works, and gets them from 0-60 far faster than doing the same thing in a procedural language, there may just be hope. I think that's true even if your work doesn't involve web development.
I'm not so sure that bringing up the "real world" would be as much a selling point as a working framework for writing good apps, because it turns out that, especially in statically typed languages like C# and Java, modeling the real world often requires tortuous abstractions. You can see a concrete example of the difficulty of modeling the real world by looking at thousands of people struggling to model something as ostensibly simple as the geometric abstraction of "shape" (shape, ellipse, circle).
All programming paradigms have the same goal: hiding unneeded complexity.
Some problems are easily solved with an imperative paradigm, like your friend uses. Other problems are easily solved with an object-oriented paradigm. There are many other paradigms. The main ones (logic programming, functional programming, and imperative programming) are all equivalent to each other; object-oriented programming is usually thought as an extension to imperative programming.
Object-oriented programming is best used when the programmer is modeling items that are similar, but not the same. An imperative paradigm would put the different kinds of models into one function. An object-oriented paradigm separates the different kinds of models into different methods on related objects.
Your colleague seems to be stuck in one paradigm. Good luck.
To me, the power of OOP doesn't show itself until you start talking about inheritance and polymorphism.
If one's argument for OOP rests the concept of encapsulation and abstraction, well that isn't a very convincing argument for me. I can write a huge library and only document the interfaces to it that I want the user to be aware of, or I can rely on language-level constructs like packages in Ada to make fields private and only expose what it is that I want to expose.
However, the real advantage comes when I've written code in a generic hierarchy so that it can be reused later such that the same exact code interfaces are used for different functionality to achieve the same result.
Why is this handy? Because I can stand on the shoulders of giants to accomplish my current task. The idea is that I can boil the parts of a problem down to the most basic parts, the objects that compose the objects that compose... the objects that compose the project. By using a class that defines behavior very well in the general case, I can use that same proven code to build a more specific version of the same thing, and then a more specific version of the same thing, and then yet an even more specific version of the same thing. The key is that each of these entities has commonality that has already been coded and tested, and there is no need to reimpliment it again later. If I don't use inheritance for this, I end up reimplementing the common functionality or explicitly linking my new code against the old code, which provides a scenario for me to introduce control flow bugs.
Polymorphism is very handy in instances where I need to achieve a certain functionality from an object, but the same functionality is also needed from similar, but unique types. For instance, in Qt, there is the idea of inserting items onto a model so that the data can be displayed and you can easily maintain metadata for that object. Without polymorphism, I would need to bother myself with much more detail than I currently do (I.E. i would need to implement the same code interfaces that conduct the same business logic as the item that was originally intended to go on the model). Because the base class of my data-bound object interacts natively with the model, I can instead insert metadata onto this model with no trouble. I get what I need out of the object with no concern over what the model needs, and the model gets what it needs with no concern over what I have added to the class.
Ask your friend to visualize any object in his very Room, House or City... and if he can tell a single such object which a system in itself and is capable of doing some meaningful work. Things like a button isnt doing something alone - it takes lots of objects to make a phone call. Similarly a car engine is made of the crank shaft, pistons, spark plugs. OOPS concepts have evolved from our perception in natural processes or things in our lives. The "Inside COM" book tells the purpose of COM by taking analogy from a childhood game of identifying animals by asking questions.
Design trumps technology and methodology. Good designs tend to incorporate universal principals of complexity management such as law of demeter which is at the heart of what OO language features strive to codify.
Good design is not dependant on use of OO specific language features although it is typically in ones best interests to use them.
Not only does it make
programming easier / more maintainable in the current situation for other people (and yourself)
It is already allowing easier database CRUD (Create, Update, Delete) operations.
You can find more info about it looking up:
- Java : Hibernate
- Dot Net : Entity Framework
See even how LINQ (Visual Studio) can make your programming life MUCH easier.
Also, you can start using design patterns for solving real life problems (design patterns are all about OO)
Perhaps it is even fun to demonstrate with a little demo:
Let's say you need to store employees, accounts, members, books in a text file in a similar way.
.PS. I tried writing it in a PSEUDO way :)
the OO way
Code you call:
io.file.save(objectsCollection.ourFunctionForSaving())
class objectsCollection
function ourFunctionForSaving() As String
String _Objects
for each _Object in objectsCollection
Objects &= _Object & "-"
end for
return _Objects
end method
NON-OO Way
I don't think i'll write down non-oo code. But think of it :)
NOW LET'S SAY
In the OO way. The above class is the parent class of all methods for saving the books, employees, members, accounts, ...
What happens if we want to change the way of saving to a textfile? For example, to make it compactible with a current standard (.CVS).
And let's say we would like to add a load function, how much code do you need to write?
In the OO- way you only need the add a New Sub method which can split all the data into parameters (This happens once).
Let your collegue think about that :)
In domains where state and behavior are poorly aligned, Object-Orientation reduces the overall dependency density (i.e. complexity) within these domains, which makes the resulting systems less brittle.
This is because the essence of Object-Orientation is based on the fact that, organizationally, it doesn't dustinguish between state and behavior at all, treating both uniformly as "features". Objects are just sets of features clumpled to minimize overall dependency.
In other domains, Object-Orientation is not the best approach. There are different language paradigms for different problems. Experienced developers know this, and are willing to use whatever language is closest to the domain.

The limit of OOP Paradigm in really complex system? [closed]

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I asked a question previously about Dataset vs Business Objects
.NET Dataset vs Business Object : Why the debate? Why not combine the two?
and I want to generalize the question here: where is the proof that OOP is really suitable for very complex problems ? Let's take a MMO Game Engine for example. I'm not specialist at all but as I read this article, it clearly stands that OOP is far from being enough:
http://t-machine.org/index.php/2007/11/11/entity-systems-are-the-future-of-mmog-development-part-2/
It concludes:
Programming well with Entity Systems is very close to programming with a Relational Database. It would not be unreasonable to call ES’s a form of “Relation Oriented Programming”.
So isn't OOP trying to get rid off something that is here to stay ?
OOP is non-linear, Relational is linear, both are necessary depending on the part of a system so why try to eliminate Relational just because it isn't "pure" Object. Is OOP an end by itself ?
My question is not is OOP usefull. OOP is usefull, my question is rather why the purists want to do "pure" OOP ?
As the author of the linked post, I thought I'd throw in a couple of thoughts.
FYI: I started seriously (i.e. for commercial work) using OOP / ORM / UML in 1997, and it took me about 5 years of day to day usage to get really good at it IMHO. I'd been programming in ASM and non-OOP languages for about 5 years by that point.
The question may be imperfectly phrased, but I think it's a good question to be asking yourself and investigating - once you understand how to phrase it better, you'll have learnt a lot useful about how this all hangs together.
"So isn't OOP trying to get rid off something that is here to stay ?"
First, read Bjarne's paper here: http://www.stroustrup.com/oopsla.pdf
IMHO, no-one should be taught any OOP without reading that paper (and re-reading after they've "learnt" OOP). So many many people misunderstand what they're dealing with.
IME, many university courses don't teach OOP well; they teach people how to write methods, and classes, and how to use objects. They teach poorly why you would do these things, where the ideas come from, etc. I think much of the mis-usage comes from that: almost a case of the blind leading the blind (they aren't blind in "how" to use OOP, they're just blind in "why" to use OOP).
To quote from the final paragraphs of the paper:
"how you support good programming techniques and good design techniques matters more than labels and buzz words. The fundamental idea is simply to improve design and programming through abstraction. You want to hide details, you want to exploit any commonality in a system, and you want to make this affordable.
I would like to encourage you not to make object-oriented a meaningless term. The notion of ‘‘object-oriented’’ is too frequently debased:
– by equating it with good,
– by equating it with a single language, or
– by accepting everything as object-oriented.
I have argued that there are–and must be–useful techniques beyond object-oriented programming and design. However, to avoid being totally misunderstood, I would like to emphasize that I wouldn’t attempt a serious project using a programming lan-
guage that didn’t at least support the classical notion of object-oriented programming. In addition to facilities that support object-oriented programming, I want –and C++ provides features that go beyond those in their support for direct expression of concepts and relationships."
Now ... I'd ask you ... of all the OOP programmers and OOP projects you've seen, how many of them can honestly claim to have adhered to what Bjarne requests there?
IME, less than the majority.
Bjarne states that:
"The fundamental idea is simply to improve design and programming through abstraction"
...and yet many people invent for themselves a different meaning, something like:
"The fundamental idea is that OOP is good, and everything-not-OOP is inferior"
Programmers who have programmed sequentially with ASM, then later ASM's, then pascal, then C, then C++, and have been exposed to the chaos that was programming pre-encapsulation etc tend to have better understanding of this stuff. They know why OOP came about, what it was trying to solve.
Funnily enough, OOP was not trying to solve every programming problem. Who'd have htought it, to say how it's talked about today?
It was aimed at a small number of problems that were hugely dangerous the bigger your project got, and which it turned out to be somewhere between "good" and "very good" at solving.
But even some of them it isn't any better than merely "good" at solving; there are other paradigms that are better...
All IMHO, of course ;)
Systems of any notable complexity are not linear. Even if you worked really hard to make a system one linear process, you're still relying on things like disks, memory and network connections that can be flaky, so you'll need to work around that.
I don't know that anyone thinks OOP is the final answer. It's just a way of dealing with complexity by trying to keep various problems confined to the smallest possible sphere so the damage they do when they blow up is minimized. My problem with your question is that it assumes perfection is possible. If it were, I could agree OOP isn't necessary. It is for me until someone comes up with a better way for me to minimize the number of mistakes I make.
Just read yr article about Entity Systems, which compares ES to OOP, and it is flagrantly wrong about several aspects of OOP. for e.g., When there are 100 instances of a class, OOP does not mandate that there be 100 copies of the classes methods loaded in memory, only one is necessary. Everything that ES purports to be able to do "better" than OOP because it has "Components", and "Systems", OOP supports as well using interfaces and static classes, (and/or Singletons).
And OOP more naturally fits with the real-world, as any real or imagined Problem Domain, consisting of multiple physical and/or non-physical items and abstractions, and the relationships between them, can be modeled with an appropriately designed hiearchical OOP class structure.
What we try to do is put an OO style on top of a relational system. In C# land this gets us a strongly typed system so that everything from end to end can be compiled and tested. The database has a hard time being tested, refactored, etc. OOP allows us to organize our application into layers and hiearchies which relational doesn't allow.
Well you've got a theoretical question.
Firstly let me agree with you that OOP is not a solve-all solution. It's good for somethings, it's not good for others. But that doesn't mean it doesn't scale up. Some horribly complex and huge systems have been designed using OOP.
I think OOP is so popular because it deserves to be. It solves some problems rather wonderfully, it is easy to think in terms of Objects because we can do that without re-programming ourselves.
So until we can all come up with a better alternatives that actually works in practical life, I think OOP is a pretty good idea and so are relational databases.
There is really no limit to what OOP can deal with - just as there is no real limit to what C can deal with, or assembler for that matter. All are Turing-complete, which is all you really need.
OOP simply gives you a higher-level way of breaking down the program, just as C is a higher-level than assembler.
The article about entity systems does not say that OO cannot do this - in fact, it sounds like they are using OOP to implement their Entities, Components, etc. In any complex domain there will be different ways of breaking it down, and using OOP you can break it down to the object/class level at some point. This does not preclude having higher-level conceptual frameworks which are used to design the OOP system.
The problem isn't the object oriented approach in most situations, the problem is performance and actual development of the underlying hardware.
The OO paradigm approach software development by providing us with a metaphor of the real world, were we have concepts which defines the common accepted and expected properties and behaivour of real objects in the world. Is the way that humans model things and we're able to solve most of the problems with it.
In theory you can define every aspect of a game, system or whatever using OO. In practice if you do, your program will simply behave too slow so the paradigm is messed up by optimizations which trade the simplicity of the model from performance.
In that way, relational databases are not object oriented so we build an object oriented layer between our code and the database... by doing so you lost some of the performance of the database and some of its expressiveness because, from the point of view of OO paradigm a relational database is a full class, is an very complex object that provides information.
From my point of view OO is an almost perfect approach in the theoretical sense of the word, as it maps closely to the way we, humans, think, but it doesn't fit well with the limited resources of the computational development... so we take shortcuts. At the and, performance is far more important than theoretical organization or clearness so this shortcuts become standards or usual practices.
That is, we are adapting the theoretical model to our current limitations. In the times of cobol in the late 70's object oriented was simply impossible... it would imply to many aspects and too little performance so we used a simplified approach, so simplified you didn't have objects or class, you had variables ... but the concept was, in that time, the same. Groups of variables described related concepts, properties that today will feet into an object. Control sequences based on a variable value where used to replace class hierarchies and so on.
I think we've been using OOP for a long time and that we'll continue using it for a long time. As hardware capabilities improve we'll be able to unsimplify the model so that it becomes more adaptable. If I describe perfectly (almost) the concept of a cat (which involves a lot of describing for a lot of concepts involved) that concept will be able to be reused everywhere... the problem here is not, as I've said, with the paradigm itself but with our limitations to implement it.
EDIT: To answer the question about why use pure OO. Every "science" wants to have a complete model to represent things. We have two physic models to describe nature, one at the microscopic level and one for the macroscopic one, and we want to have just one because it simplifies things it provides us with a better way to prove, test and develop things. With OO the same process applies. You can't analytically test and prove a system if the system doesn't follow a precise set of rules. If you are changing between paradigms in a program then your program cannot be properly analized, it has to be disected in each one, analized and then analized again to see that the interactions are correct. It makes a lot more difficult to understand a system because in fact you have two or three system that interact in different ways.
Guys, isn't the question more about ORM than OOP? OOP is a style of programming - the thing that actually gets compared is a Relational Database mapped onto objects.
OOP is actually more than just the ORM! It's also not just the inheritance and polymorphism! It's an extremly wide range of design patterns and above all it's the way we think about programming itself.
Jorge: it's ok that you've pointed out the opitimization part - what you didn't add is that this step should be done last and in 99% cases the slow part is not the OOP.
Now plain and simple: the OOP style with all the principals added to it (clean code, use of design patterns, not to deep inheritance structures and let's not forget unit testing!) it a way to make more people understand what you wrote. That in turn is needed for companies to keep their bussiness secure. That's also a recepie for small teams to have better understanding with the community. It's like a common meta language on top of the programming language itself.
It's always easier to talk about concepts from a purists point of view. Once you're faced with a real life problem things get trickier and the world is no longer just black and white. Just like the author of the article is very thorough in pointing out that they're not doing OOP the "OOP purist" tells you that OOP is the only way to go. The truth is somewhere in between.
There is no single answer, as long as you understand the different ways (OOP, entity systems, functional programming and many more) of doing things and can give good reason for why you're choosing one over the other in any given situation you're more likely to succeed.
About Entity Systems. It's an interesting conception but it brings nothing really new. For example it states:
OOP style would be for each Component to have zero or more methods, that some external thing has to invoke at some point. ES style is for each Component to have no methods but instead for the continuously running system to run it’s own internal methods against different Components one at a time.
But isn't it same as Martin Fowler's anti-pattern called "Anemic Domain Model" (which is extensively used nowadays, in fact) link ?
So basically ES is an "idea on the paper". For people to accept it, it MUST be proven with working code examples. There is not a single word in the article on how to implement this idea on practice. Nothing said about scalability concerns. Nothing said about fault tolerance...
As for your actual question I don't see how Entity Systems described in article can be similar to relational databases. Relational databases have no such thing as "aspects" that are described in the article. In fact, relational - based on tables data structure - is very limited when it comes to working with hierarchical data, for example. More limited than for example object databases...
Could you clarify what exactly you are trying to compare and prove here? OOP is a programming paradigm, one of the many. It's not perfect. It's not a silver bullet.
What does "Relation Oriented Programming" mean? Data-centric? Well, Microsoft was moving towards more data-centric style of programming until they given up on Linq2Sql and fully focused on their O/RM EntityFramework.
Also relational databases isn't everything. There is many different kinds of database architectures: hierarchical databases, network databases, object databases ect. And those can be even more efficient than relational. Relational are so popular for nearly the same reasons why OOP is so popular: it's simple, very easy to understand and most often efficient enough.
Ironically when oo programming arrived made it much easier to build larger systems, this was reflected in the ramp up in software to market.
Regarding scale and complexity, with good design you can build pretty complex systems.
see ddd Eric Evans for some principle patterns on handling complexity in oo.
However not all problem domains are best suited to all languages, if you have the freedom to choose a language choose one that suits your problem domain. or build a dsl if that's more appropriate.
We are software engineers after all, unless there is someone telling you how to do your job, just use the best tools for the job, or write them :)

Does procedural programming have any advantages over OOP?

[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!

Database Guy Asks: Object-Oriented Design Theory?

I've worked with designing databases for a loooong time, and these days I'm working in C# too. OO makes sense to me, but I don't feel that I have a good grounding in the deep theory of OO design.
In database land, there's a lot of theory around how to design the structure of a database, the main notion being normalisation. Normalisation directly steers the structure of a database and to some extent dictates how to arrange entities in a database.
Are there any similar concepts behind how to design the structure of an Object-Oriented program?
What I'm reaching for is one or more underlying theoretical principles which naturally guide the developer into the "correct" design for the solution to a given problem.
Where can I look to find out more?
Is there a go-to work I should read?
Update:
Thanks to everyone for their answers.
What I'm reading seems to say that there is no "Grand Theory of OO Design", but there are a bunch of important principles - which are largely exemplified by design patterns.
Thanks again for your answers :)
Be careful some of the design patterns literature.
There are are several broad species of class definitions. Classes for persistent objects (which are like rows in relational tables) and collections (which are like the tables themselves) are one thing.
Some of the "Gang of Four" design patterns are more applicable to active, application objects, and less applicable to persistent objects. While you wrestle through something like Abstract Factory, you'll be missing some key points of OO design as it applies to persistent objects.
The Object Mentor What is Object-Oriented Design? page has mich of you really need to know to transition from relational design to OO design.
Normalization, BTW, isn't a blanket design principle that always applies to relational databases. Normalization applies when you have update transactions, to prevent update anomalies. It's a hack because relational databases are passive things; you either have to add processing (like methods in a class) or you have to pass a bunch of rules (normalization). In the data warehouse world, where updates are rare (or non-existent) that standard normalization rules aren't as relevant.
Consequently, there's no "normalize like this" for object data models.
In OO Design, perhaps the most important rule for designing persistent objects is the Single Responsibility Principle.
If you design your classes to have good fidelity to real-world objects, and you allocate responsibilities to those classes in a very focused way, you'll be happy with your object model. You'll be able to map it to a relational database with relatively few complexities.
Turns out, that when you look at things from a responsibility point of view, you find that 2NF and 3NF rules fit with sound responsibility assignment. Unique keys still matter. And derived data becomes the responsibility of a method function, not a persistent attribute.
The book "Design Patterns" is your next step.
http://www.amazon.com/Design-Patterns-Object-Oriented-Addison-Wesley-Professional/dp/0201633612
But, you don't have to use an OO approach to everything. Don't be religious about it. If a more procedural approach feels more straitforward, then go with that. People new to OO tend to overdue it for a while.
I think Agile Software Development, Principles, Patterns, and Practices is quite good.
It provides a lot of in-depth disccusion of OO principles listed here:
The principles of Object Oriented Design and Dependency Management
SRP — The Single Responsibility Principle
OCP — The Open Closed Principle
LSP — The Liskov Substitution Principle
DIP — The Dependency Inversion Principle
ISP — The Interface Segregation Principle
REP — The Reuse Release Equivalency Principle
CCP — The Common Closure Principle
CRP — The Common Reuse Principle
ADP — The Acyclic Dependencies Principle
SDP — The Stable Dependencies Principle
SAP — The Stable Abstractions Principle
If you're used to building normalized databases, then Object Oriented design should come naturally to you. Your class structures will end up looking a lot like your data structure, with the obvious exception that association tables turn into lists and lookup tables turn into enums within your classes.
All together, I'd say you're a lot better off coming into OO design with a background in Relational Databases than you would be going the other direction.
If you want to really get to grips with O-O, go play with Smalltalk. ST is a pure OO language, and quite in-your-face about it. Once you get over the paradigm hump you've learned OO as you can't really do Smalltalk without it. This is how I first learned OO.
Check the results of this. Learn from each question.
I really liked Head First Design Patterns, which is very approachable, and the excellent Object oriented Design Heuristics by Arthur J. Riel
This site lists 101 title... design patterns, refactoring and other... Have a look at it.. It will be a good starting point...
Go for Object Thinking by David West. An interesting read..
You're from the dark side though.. as per the book;) Database thinking has been the curse of OO programmers all over. They're opposite ends of a spectrum. For instance
Database thinking values the data attribues over everything else.. normalization and creating types based on how they fit into the DB Schema OR the ER diagram.. OO thinking creates types based on behavior and collaboration and does not recognize the data attributes as all important.
Databases come from the scientific people who value formalization and method over everything else. OO comes from the people who use heuristics and rules of thumb and value individuality and social interaction over a hard and fast process.
The point being a COBOL programmer can write COBOL programs even after moving onto a OO Language. Check out any book like Thinking in Java for the first section which invariably details out the tenets of OO (Apprentice).. Follow it up with Object Thinking (journeyman) and in due time.. a master.
Model your objects by keeping real world objects in mind.
We are currently developing automation software for machines. One of those machines has two load ports for feeding it raw material, while all others have only one. In all modules so far, we had the information of the ports (current settings, lot number currently assigned to it etc) as members in the class representing the machine.
We decided to create a new class that holds the information of the ports, and add two LoadPort members to this MachineXY class. If we had thought about it before, we would have done the same for all those single port machines...
You should look at UML, which is an entire process given to OOD.
I'd recommend getting a book (or a couple), because the theory is quite large, most people pick and choose the techniques most appropriate for the project at hand.
Start reading about design patters, from say Martin Fowler. :)
They are the most practical use of OOP.
I am guess you mean OO in the database world.
Object-oriented databases which store objects never did really catch one so you are currently looking mapping objects to relational database. ORM or Object-relational mapping is the term used to describe the software that does this mapping. Ideally this gives you the best of both worlds where developers can internact with the objects and in the database everything is stored in relational tables where standard tuning can take place.
in DBA slang: object-oriented design is nothing else but properly normalized data behind safe operation interfaces, safe meaning, look at the operations, not the data directly

How do I break my procedural coding habits? [closed]

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I recently read an interesting comment on an OOP related question in which one user objected to creating a "Manager" class:
Please remove the word manager
from your vocabulary when talking
about class names. The name of the
class should be descriptive of its'
purpose. Manager is just another word
for dumping ground. Any
functionality will fit there. The word
has been the cause of many extremely
bad designs
This comment embodies my struggle to become a good object-oriented developer. I have been doing procedural code for a long time at an organization with only procedural coders. It seems like the main strategy behind the relatively little OO code we produce is to break the problem down into classes that are easily identifiable as discrete units and then put the left over/generalized bits in a "Manager" class.
How can I break my procedural habits (like the Manager class)? Most OO articles/books, etc. use examples of problems that are inherently easy to transform into object groups (e.g., Vehicle -> Car) and thus do not provide much guidance for breaking down more complex systems.
First of all, I'd stop acting like procedural code is wrong. It's the right tool for some jobs. OO is also the right tool for some jobs. So is functional. Each paradigm is just a different point of view of computation, and exists because it's convenient for certain problems, not because it's the only right way to program. In principle, all three paradigms are mathematically equivalent, so use whichever one best maps to the problem domain. IMHO, if using a multiparadigm language it's even ok to blend paradigms within a module if different subproblems are best modeled by different worldviews.
Secondly, I'd read up on design patterns. It's hard to understand OO without some examples of the real-world problems it's good for solving. Head First Design Patterns is a good read, as it answers a lot of the "why" of OO.
Becoming good at OO takes years of practice and study of good OO code, ideally with a mentor. Remember that OO is just one means to an end. That being said, here are some general guidelines that work for me:
Favor composition over inheritance. Read and re-read the first chapter of the GoF book.
Obey the Law of Demeter ("tell, don't ask")
Try to use inheritance only to achieve polymorphism. When you extend one class from another, do so with the idea that you'll be invoking the behavior of that class through a reference to the base class. ALL the public methods of the base class should make sense for the subclass.
Don't get hung up on modeling. Build a working prototype to inform your design.
Embrace refactoring. Read the first few chapters of Fowler's book.
The single responsibility principle helps me break objects into manageable classes that make sense.
Each object should do one thing, and do it well without exposing how it works internally to other objects that need to use it.
A 'manager' class will often:
Interogate something's state
Make a decision based on that state
As an antidote or contrast to that, Object-Oriented design would encourage you to design class APIs where you "tell don't ask" the class itself to do things itself (and to encapsulate its own state): for more about "tell don't ask" see e.g. here and here (and maybe someone else has a better explanation of "tell don't ask" but these are first two articles that Google found for me).
It seems like the main strategy the little OO code we produce is to break the problem down into classes that are easily identifiable as discrete units and then put the left over/generalized bits in a "Manager" class.
That may well be true even at the best of times. Coplien talked about this towards the end of his Advanced C++: Programming Styles and Idioms book: he said that in a system, you tend to have:
Self-contained objects
And, "transactions", which act on other objects
Take, for example, an airplane (and I'm sorry for giving you another vehicular example; I'm paraphrasing him):
The 'objects' might include the ailerons, the rudder, and the thrust
The 'manager' or autpilot would implement various commands or transactions
For example, the "turn right" transaction includes:
flaps.right.up()
flaps.left.down()
rudder.right()
thrust.increase()
So I think it's true that you have transactions, which cut across or use the various relatively-passive 'objects'; in an application, for example, the "whatever" user-command will end up being implemented by (and therefore, invoking) various objects from every layer (e.g. the UI, the middle layer, and the DB layer).
So I think it's true that to a certain extent you will have 'bits left over'; it's a matter of degree though: perhaps you ought to want as much of the code as possible to be self-contained, and encapsulating, and everything ... and the bits left over, which use (or depend on) everything else, should be given/using an API which hides as much as possible and which does as much as possible, and which therefore takes as much responsibility (implementation details) as possible away from the so-called manager.
Unfortunately I've only read of this concept in that one book (Advanced C++) and can't link you to something online for a clearer explanation than this paraphrase of mine.
Reading and then practicing OO principles is what works for me. Head First Object-Oriented Analysis & Design works you through examples to make a solution that is OO and then ways to make the solution better.
You can learn good object-oriented design principles by studying design patterns. Code Complete 2 is a good book to read on the topic. Naturally, the best way to ingrain good programming principles into your mind is to practice them constantly by applying them to your own coding projects.
How can I break my procedural habits (like the Manager class)?
Make a class for what the manager is managing (for example, if you have a ConnectionManager class, make a class for a Connection). Move everything into that class.
The reason "manager" is a poor name in OOP is that one of the core ideas in OOP is that objects should manage themselves.
Don't be afraid to make small classes. Coming from a procedural background, you may think it isn't worth the effort to make a class unless it's a thousand lines of code and is some core concept in your domain. Think smaller. A ten line class is totally valid. Make little classes where you see they make sense (a Date, a MailingAddress) and then work your way up by composing classes out of those.
As you start to partition little pieces of your codebase into classes, the remaining procedural code soup will shrink. In that shrinking pool, you'll start to see other things that can be classes. Continue until the pool is empty.
How many OOP programmers does it take to change a light bulb?
None, the light bulb changes itself.
;)
You can play around with an OO language that has very bad procedural support like Smalltalk. The message sending paradigm will force you into OO thinking.
i think you should start it with a good plan.
planning using CLASS Diagrams would be a good start.
you should identify the ENTITIES needed in the applicaiton,
then define each entitie's ATTRIBUTES, and METHODS.
if there are repeated ones, you could now re-define your entities
in a way that inheritance could be done, to avoid redundancy.
:D.
I have a three step process, this is one that I have gone through successfully myself. Later I met an ex-teacher turned programmer (now very experienced) who explained to me exactly why this method worked so well, there's some psychology involved but it's essentially all about maintaining control and confidence as you learn. Here it is:
Learn what test driven development (TDD) is. You can comfortably do this with procedural code so you don't need to start working with objects yet if you don't want to. The second step depends on this.
Pick up a copy of Refactoring: Improving the Design of Existing Code by Martin Fowler. It's essentially a catalogue of little changes that you can make to existing code. You can't refactor properly without tests though. What this allows you to do is to mess with the code without worrying that everything will break. Tests and refactoring take away the paranoia and sense that you don't know what will happen, which is incredibly liberating. You left to basically play around. As you get more confident with that start exploring mocks for testing the interactions between objects.
Now comes the big that most people, mistakenly start with, it's good stuff but it should really come third. At this point you can should reading about design patterns, code smells (that's a good one to Google) and object oriented design principles. Also learn about user stories or use cases as these give you good initial candidate classes when writing new applications, which is a good solution to the "where do I start?" problem when writing apps.
And that's it! Proven goodness! Let me know how it goes.
My eureka moment for understanding object-oriented design was when I read Eric Evans' book "Domain-Driven Design: Tackling Complexity in the Heart of Software". Or the "Domain Driven Design Quickly" mini-book (which is available online as a free PDF) if you are cheap or impatient. :)
Any time you have a "Manager" class or any static singleton instances, you are probably building a procedural design.