OOP vs Functional Programming vs Procedural [closed] - oop

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What are the differences between these programming paradigms, and are they better suited to particular problems or do any use-cases favour one over the others?
Architecture examples appreciated!

All of them are good in their own ways - They're simply different approaches to the same problems.
In a purely procedural style, data tends to be highly decoupled from the functions that operate on it.
In an object oriented style, data tends to carry with it a collection of functions.
In a functional style, data and functions tend toward having more in common with each other (as in Lisp and Scheme) while offering more flexibility in terms of how functions are actually used. Algorithms tend also to be defined in terms of recursion and composition rather than loops and iteration.
Of course, the language itself only influences which style is preferred. Even in a pure-functional language like Haskell, you can write in a procedural style (though that is highly discouraged), and even in a procedural language like C, you can program in an object-oriented style (such as in the GTK+ and EFL APIs).
To be clear, the "advantage" of each paradigm is simply in the modeling of your algorithms and data structures. If, for example, your algorithm involves lists and trees, a functional algorithm may be the most sensible. Or, if, for example, your data is highly structured, it may make more sense to compose it as objects if that is the native paradigm of your language - or, it could just as easily be written as a functional abstraction of monads, which is the native paradigm of languages like Haskell or ML.
The choice of which you use is simply what makes more sense for your project and the abstractions your language supports.

I think the available libraries, tools, examples, and communities completely trumps the paradigm these days. For example, ML (or whatever) might be the ultimate all-purpose programming language but if you can't get any good libraries for what you are doing you're screwed.
For example, if you're making a video game, there are more good code examples and SDKs in C++, so you're probably better off with that. For a small web application, there are some great Python, PHP, and Ruby frameworks that'll get you off and running very quickly. Java is a great choice for larger projects because of the compile-time checking and enterprise libraries and platforms.
It used to be the case that the standard libraries for different languages were pretty small and easily replicated - C, C++, Assembler, ML, LISP, etc.. came with the basics, but tended to chicken out when it came to standardizing on things like network communications, encryption, graphics, data file formats (including XML), even basic data structures like balanced trees and hashtables were left out!
Modern languages like Python, PHP, Ruby, and Java now come with a far more decent standard library and have many good third party libraries you can easily use, thanks in great part to their adoption of namespaces to keep libraries from colliding with one another, and garbage collection to standardize the memory management schemes of the libraries.

These paradigms don't have to be mutually exclusive. If you look at python, it supports functions and classes, but at the same time, everything is an object, including functions. You can mix and match functional/oop/procedural style all in one piece of code.
What I mean is, in functional languages (at least in Haskell, the only one I studied) there are no statements! functions are only allowed one expression inside them!! BUT, functions are first-class citizens, you can pass them around as parameters, along with a bunch of other abilities. They can do powerful things with few lines of code.
While in a procedural language like C, the only way you can pass functions around is by using function pointers, and that alone doesn't enable many powerful tasks.
In python, a function is a first-class citizen, but it can contain arbitrary number of statements. So you can have a function that contains procedural code, but you can pass it around just like functional languages.
Same goes for OOP. A language like Java doesn't allow you to write procedures/functions outside of a class. The only way to pass a function around is to wrap it in an object that implements that function, and then pass that object around.
In Python, you don't have this restriction.

For GUI I'd say that the Object-Oriented Paradigma is very well suited. The Window is an Object, the Textboxes are Objects, and the Okay-Button is one too. On the other Hand stuff like String Processing can be done with much less overhead and therefore more straightforward with simple procedural paradigma.
I don't think it is a question of the language neither. You can write functional, procedural or object-oriented in almost any popular language, although it might be some additional effort in some.

In order to answer your question, we need two elements:
Understanding of the characteristics of different architecture styles/patterns.
Understanding of the characteristics of different programming paradigms.
A list of software architecture styles/pattern is shown on the software architecture article on Wikipeida. And you can research on them easily on the web.
In short and general, Procedural is good for a model that follows a procedure, OOP is good for design, and Functional is good for high level programming.
I think you should try reading the history on each paradigm and see why people create it and you can understand them easily.
After understanding them both, you can link the items of architecture styles/patterns to programming paradigms.

I think that they are often not "versus", but you can combine them. I also think that oftentimes, the words you mention are just buzzwords. There are few people who actually know what "object-oriented" means, even if they are the fiercest evangelists of it.

One of my friends is writing a graphics app using NVIDIA CUDA. Application fits in very nicely with OOP paradigm and the problem can be decomposed into modules neatly. However, to use CUDA you need to use C, which doesn't support inheritance. Therefore, you need to be clever.
a) You devise a clever system which will emulate inheritance to a certain extent. It can be done!
i) You can use a hook system, which expects every child C of parent P to have a certain override for function F. You can make children register their overrides, which will be stored and called when required.
ii) You can use struct memory alignment feature to cast children into parents.
This can be neat but it's not easy to come up with future-proof, reliable solution. You will spend lots of time designing the system and there is no guarantee that you won't run into problems half-way through the project. Implementing multiple inheritance is even harder, if not almost impossible.
b) You can use consistent naming policy and use divide and conquer approach to create a program. It won't have any inheritance but because your functions are small, easy-to-understand and consistently formatted you don't need it. The amount of code you need to write goes up, it's very hard to stay focused and not succumb to easy solutions (hacks). However, this ninja way of coding is the C way of coding. Staying in balance between low-level freedom and writing good code. Good way to achieve this is to write prototypes using a functional language. For example, Haskell is extremely good for prototyping algorithms.
I tend towards approach b. I wrote a possible solution using approach a, and I will be honest, it felt very unnatural using that code.

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Why use classes instead of functions? [closed]

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I do know some advantages to classes such as variable and function scopes, but other than that is just seems easier to me to have groups of functions rather than to have many instances and abstractions of classes. So why is the "norm" to group similar functions in a class?
Simple, non-OOP programs may be one
long list of commands. More complex
programs will group lists of commands
into functions or subroutines each of
which might perform a particular task.
With designs of this sort, it is
common for the program's data to be
accessible from any part of the
program. As programs grow in size,
allowing any function to modify any
piece of data means that bugs can have
wide-reaching effects.
In contrast, the object-oriented
approach encourages the programmer to
place data where it is not directly
accessible by the rest of the program.
Instead the data is accessed by
calling specially written functions,
commonly called methods, which are
either bundled in with the data or
inherited from "class objects" and act
as the intermediaries for retrieving
or modifying those data. The
programming construct that combines
data with a set of methods for
accessing and managing those data is
called an object.
Advantages of OOP programming:
MAINTAINABILITY Object-oriented programming methods make code more maintainable. Identifying the source of errors is easier because objects are self-contained.
REUSABILITY Because objects contain both data and methods that act on data, objects can be thought of as self-contained black boxes. This feature makes it easy to reuse code in new systems.Messages provide a predefined interface to an object's data and functionality. With this interface, an object can be used in any context.
SCALABILITY Object-oriented programs are also scalable. As an object's interface provides a road map for reusing the object in new software, and provides all the information needed to replace the object without affecting other code. This way aging code can be replaced with faster algorithms and newer technology.
The point of OOP is not to 'group similar functions in a class'. If this is all you're doing then you're not doing OOP (despite using an OO language). Having classes instead of just a bunch of functions has a side effect of 'variable and function scopes' that you mention, but I see it just as a side effect.
OOP is about such concepts as encapsulation, inheritance, polymorphism, abstraction and many others. It is a specific way of software design, a specific way of mapping a problem to a software solution.
Grouping functions in a class is by no means the norm. Let me share some of the things I have learned through experimentation with different languages and paradigms.
I think the core concept here is that of a namespace. Namespaces are so useful that they are present in almost on any programming language.
Namespaces can help you overcome some common problems and model various patterns that appear in many domains, e.g., avoiding name collisions, hiding details, representing hierarchies, define access control, grouping related symbols (functions or data), define a context or scope ... and I'm sure there are more applications.
Classes are a type of namespace, and the specific properties of classes vary from language to language and sometimes from version to version of the same language, e.g., some provide access modifiers, some do not; some allow inheritance from multiple classes, others do not. People have been trying to find the magic mix of features that will be the most useful and that in part explains the plethora of available options in different programming languages.
So, why use classes, because they help solve certain kinds of problems in a way that seems natural or maybe intuitive. Every time we write a computer program we're trying to capture the essence of the problem and if the problem can be modeled by using some of the patterns mentioned above then it makes perfect sense to use those features of a language that help you do that.
As the problem becomes better understood you might realize that certain parts of the program could be better implemented by using a different paradigm/feature/pattern and then it's time for refactoring. Most programs I have had the chance to work on keep evolving until either the money/resources run out or when we arrive at the point of diminishing returns, many times you have something that's good enough for now and there's little incentive to keep working on it.
It's not the norm, it's just one way of doing it. Classes group methods (functions) AND data together, based on the concept of encapsulation.
For lager projects it often becomes easier to group things this way. Many people find it easier to conceptualizes the problem with objects.
There are many reasons to use classes, not the least of which is encapsulation of logic. Objects more closely match the world we live in, and are thus often more intuitive than other methodologies. Consider a car, a car has properties like body color, interior color, engine horsepower, features, current mileage, etc.. It also has methods, like Start (), TurnRight(.30), ApplyBrakes(.50). It has events like the ding when you open your car door with the keys in the ignition.
Probably the biggest reason is that most applications seem to have a graphical component these days and most of the libraries for graphical user interface are implemented with object models.
Polymorphism is probably a big reason, too. The ability to treat multiple types of objects generically is quite helpful.
If you are a mathematician, a functional style may be more intuitive, ML, F#. If you’re interacting with data in a predictable format, a declarative style would be better like SQL or LINQ.
In simple words, it seems to me that (apart from everything everyone is saying) that classes are best suited for large projects, especially those implemented by more than one programmer to facilitate keeping things tidy; as using functions in such situations can become rather cumbersome.
Otherwise, for simple programs/projects that you would implement yourself to do one thing or another, then functions would do nicely.

Mathematica OO System ( or alternatives )?

OO system is a free, open source package for OOP in Mathematica. By using OO-System I hope to benefit from the best of both worlds (OOP/Functional).
What are the do's and don'ts of OO
System for Mathematica?
Are you aware of (better) open
source alternatives?
Are you willing to show some of your
OO-system classes?
Any remarks about OOP in general with
Mathematica ?
A disclaimer: I have not used any of the existing OO mma extensions (and OO System in particular), so this post is based on general arguments (but I used OO heavily when worked in Java, and used some OO elements in mma, which I implemented myself). I agree with the opinion that OO is a moving target, so you have to be more specific in terms of features you want, to get a more useful answer. It also greatly depends on what are your goals - do you want to simplify your own life and make your own project scale, or do you want to simplify the communication for the project which is going to be developed by several (many) developers, and enforce certain rules and protocols (coding standards, best practices, design patterns, whatever), or do you want OO to reuse existing libraries.
I'd argue that most of OOP use in the industry fall into the second and third categories. If this is also your case (which I suspect it is not), then it may make sense to use OOP in Mathematica, although even this is not clear. WolframAlpha, for example, has tens of millions of lines of code in its codebase, and AFAIK no OO system was used there. If you want the benefits for the solo developer, then I'd choose those features of OO that I like and implement them myself - i.e., create your own object model. This is not too difficult in Mathematica.
It would make much more sense to use some specific OO extension of Mathematica if there would be a large number of well-tested open-source libraries built using this extension, with an easy deployment mechanism. I am not aware of any significant mma code base (libraries) built with any of existing OO mma extensions (which could as well be due to my ignorance). So if you need OO to reuse existing libraries, then things like J/Link or .Net/Link may serve you better, since you will have access to all of Java or .Net.
If you want the techniques to scale your project, then OO is not your only friend. While this is probably not a very well explored territory for mma (except may be by WRI), some techniques from other functional languages such as closures, LISP macros, run-time code generation, etc, may well be applicable to mma. For example, one of the mma projects I am working on has more than 40 packages and more than 10 thousand lines of mma code, and it is quite managable (with WorkBench). I am using closures and macros a lot, and also some OO features, but not any generic OO extension. The important things are information hiding, lose coupling, composability and testability, and again, OO is not the only way to do that.
IMO, one very nice thing that could be accomplished by an OO-capable language layer in mma (perhaps, Python-like) would be to hide the complexities of the evaluator and pattern-matcher, because in many cases those are not needed and may be confusing to less experienced users. I was (and still am) missing such language layer quite a bit at times. The designer of such layer will face a hard task of making it really well integrated with the rest of mma. Apart from that, I see the two major obstacles for a generic OO system built in the top-level mma: slow performance and no automatic garbage collection. I think, until these are solved, they rule out the heavy production use of OOP at the lower-level (creating millions of objects etc). Some features of OOP may still be quite useful for high-level project architecture, but as I said, they are easily implemented. This is not to say you should not try existing OO extensions, I'd just weight their benefits specifically for mma against the necessary limitations they will impose on your code.
You may also find MathOO interesting (note that I have never used it).

What is the difference between procedural and OO development?

Of course, I can explain it in whole books.
But I read a few days ago, that in a application talk, it is often asked and they expect a answer in 2-5 sentence, that should be very clear and show that you udnerstand the material.
I tried a few times to collect the answer in 2 sentence but don't get a good one.
How's about this for a succinct description:
Procedural Programming is primarily organized around "actions" and "logic".
OOP is primarily organized around "objects" and "data".
OOP takes the view that what we really care about are the objects we want to manipulate rather than the logic required to manipulate them.
Procedural Programming means dividing the problem up into smaller parts and then representing each smaller part by a definitive sub-routine,function or procedure.
OOP decomposes the problem to a set of interacting objects, each object is comprised of a number of elements, called members and methods (as opposed to variables and functions). The purpose of the object is to abstract part of the real world that we're interested in (our problem domain).
Three sentences...
Defining data structures and the behavioural logic that acts on them are central to both approaches. Being able to encapsulate associated data and behaviour allows for the concept of self-contained “Object” constructs. Pure Object Oriented Programming is where no other type of construct is required.
There is of course a mixture of both approaches in most modern high-level languages. Constructs like Value Types and Static Classes are there to provide the procedural constructs that are still very useful.
Procedure development lacks Inheritance, Encapsulation and Polymorphism. Tree paradigms that make OOP a better way of developing complex solutions.
With procedural development you often run into spaghetti code especially with complex solutions which makes it much much harder to maintain such solutions.
I'm just thinking of times when I did Turbo Pascal development and the way I do it now... A complete shift.
One more difference I felt and experienced is maintenance of code. With procedural language code maintenance goes wary but it is lot better with OO. Sometimes, changing code at some where deep down in the procedural program has blown the whole functionality itself.
Main difference is that object-oriented programming (OOP) is a programming paradigm that uses "objects" — data structures consisting of datafields and methods — and their interactions to design applications and computer programs. Programming techniques may include features such as information hiding, data abstraction, encapsulation, modularity, polymorphism, and inheritance.
In my opinion OOP is like the reality we live in. Everything around us is an object, has its own behaviour and structure.

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!

When is OOP better suited for? [closed]

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Since I started studying object-oriented programming, I frequently read articles/blogs saying functions are better, or not all problems should be modeled as objects. From your personal programming adventures, when do you think a problem is better solved by OOP?
There is no hard and fast rule. A problem is better solved with OOP when you are better at solving problems and thinking in an OO mentality. Object Orientation is just another tool which has come along through trying to make computing a better tool for solving problems.
However, it can allow for better code reuse, and can also lead to neater code. But quite often these highly praised qualities are, in-relity, of little real value. Applying OO techniques to an existing functional application could really cause a lot of problems. The skill lies in learning many different techniques and applying the most appropriate to the problem at hand.
OO is often quoted as a Nirvana-like solution to the software development, however there are many times when it is not appropriate to be applied to the issue at hand. It can, quite often, lead to over-engineering of a problem to reach the perfect solution, when often it is really not necessary.
In essence, OOP is not really Object Oriented Programming, but mapping Object Oriented Thinking to a programming language capable of supporting OO Techniques. OO techniques can be supported by languages which are not inherently OO, and there are techniques you can use within functional languages to take advantage of the benefits.
As an example, I have been developing OO software for about 20 years now, so I tend to think in OO terms when solving problems, irrespective of the language I am writing in. Currently I am implementing polymorphism using Perl 5.6, which does not natively support it. I have chosen to do this as it will make maintenance and extension of the code a simple configuration task, rather than a development issue.
Not sure if this is clear. There are people who are hard in the OO court, and there are people who are hard in the Functional court. And then there are people who have tried both and try to take the best from each. Neither is perfect, but both have some very good traits that you can utilise no matter what the language.
If you are trying to learn OOP, don't just concentrate on OOP, but try to utilise Object Oriented Analysis and general OO principles to the whole spectrum of the problem solution.
I'm an old timer, but have also programmed OOP for a long time. I am personally against using OOP just to use it. I prefer objects to have specific reasons for existing, that they model something concrete, and that they make sense.
The problem that I have with a lot of the newer developers is that they have no concept of the resources that they are consuming with the code that they create. When dealing with a large amount of data and accessing databases the "perfect" object model may be the worst thing you can do for performance and resources.
My bottom line is if it makes sense as an object then program it as an object, as long as you consider the performance/resource impact of the implementation of your object model.
I think it fits best when you are modeling something cohesive with state and associated actions on those states. I guess that's kind of vague, but I'm not sure there is a perfect answer here.
The thing about OOP is that it lets you encapsulate and abstract data and information away, which is a real boon in building a large system. You can do the same with other paradigms, but it seems OOP is especially helpful in this category.
It also kind of depends on the language you are using. If it is a language with rich OOP support, you should probably use that to your advantage. If it doesn't, then you may need to find other mechanisms to help break up the problem into smaller, easily testable pieces.
I am sold to OOP.
Anytime you can define a concept for a problem, it can probably be wrapped in an object.
The problem with OOP is that some people overused it and made their code even more difficult to understand. If you are careful about what you put in objects and what you put in services (static classes) you will benefit from using objects.
Just don't put something that doesn't belong to an object in the object because you need your object to do something new that you didn't think of initially, refactor and find the best way to add that functionality.
There are 5 criteria whether you should favor Object Oriented over Object Based,Functional or Procedural code. Remember all of these styles are available in all languages, they're styles. All of these are written in a style of "Should I favor OO in this situation?"
The system is very complex and has over approximately 9k LOC (Just an arbitrary level). -- As systems get more complex, the benefits gained by encapsulating complexity go up quite a bit. With OO, as opposed to the other techniques, you tend to encapsulate more and more of the complexity, which is very valuable at this level. Object Based or procedural should be favored before this. (This is not advocating a particular language mind you. OO C fits these features more than OO C++ in my mind, a language with a notorious reputation for leaky abstractions and an ability to eat shops with even 1 mediocre/obstinate programmer for lunch).
Your code is not operations on data (i.e. Database based or math/analysis based). Database based code is often more easily represented via procedural style. Analysis based code is often easier represented in a functional style.
Your model is a simulation of something (OO excels at simulations).
You're doing something for which the object based subtype dispatch of OO is valuable (aka, you need to send a message to all objects of a certain type and various subtypes and get an appropriate, but different, reaction out of all of them).
Your app is not multi-threaded, especially in a non-worker task method type of codebase. OO is quite problematic in programs which are multithreaded and require different threads to do different tasks. If your program is structured with one or two main threads and many worker threads doing the same thing, the muddled control flow of OO programs is easier to handle, as all of the worker threads will be isolated in what they touch and can be considered as a monolithic section of code. Consider any other paradigm actually. Functional excels at multithreading (lack of side effects is a huge boon), and object based programming can give you boons with some of the encapsulation of OO, however with more traceable procedural code in critical sections of your codebase. Procedural of course excels in this arena as well.
Some places where OO isn't so good are where you're dealing with "Sets" of data like in SQL. OO tends to make set based operations more difficult because it isn't really designed to optimally take the intersection of two sets or the superset of two sets.
Also, there are times when a functional approach would make more sense such as this example taken from MSDN:
Consider, for example, writing a program to convert an XML document into a different form of data. While it would certainly be possible to write a C# program that parsed through the XML document and applied a variety of if statements to determine what actions to take at different points in the document, an arguably superior approach is to write the transformation as an eXtensible Stylesheet Language Transformation (XSLT) program. Not surprisingly, XSLT has a large streak of functionalism inside of it
I find it helps to think of a given problem in terms of 'things'.
If the problem can be thought of as having one or more 'things', where each 'thing' has a number of attributes or pieces of information that refer to its state, and a number of operations that can be performed on it - then OOP is probably the way to go!
The key to learning Object Oriented Programming is learning about Design Pattern. By learning about design patterns you can see better when classes are needed and when they are not. Like anything else used in programming the use of classes and other features of OOP languages depends on your design and requirements. Like algorithms Design patterns are a higher level concept.
A Design Pattern plays similar role to that of algorithms for traditional programming languages. A design pattern tells you how create and combine object to perform some useful task. Like the best algorithms the best design patterns are general enough to be application to a variety of common problems.
In my opinion it is more a question about you as a person. Certain people think better in functional terms and others prefer classes and objects. I would say that OOP is better suited when it matches your internal (subjective) mental model of the world.
Object oriented code and procedural code have different extensibility points. Object oriented solutions make it easier to add new classes without modifying existing functions (see the Open-Closed Principle), while procedural code allows you to add functions without modifying existing data structures. Quite often different parts of a system require different approaches depending upon the type of change that is anticipated.
OO allows for logic related to an object to be placed within a single place (the class, or object) so that it can be decoupled and easier to debug and maintain.
What I have observed, is that every app is a combination of OO and procedural code, where the procedural code is the glue that binds all your objects together (at the very least, the code in your main function). The more you can turn your procedural code into OO, the easier it will be to maintain yor code.
Why OOP is used for programming:
Its flexibility – OOP is really flexible in terms of use implementations.
It can reduce your source codes by more than 99.9% – it may sound like I’m over exaggerating, but it is true.
It’s much easier in implementing security – We all know that security is one of the vital requirements when it comes to web development. Using OOP can ease the security implementations in your web projects.
It makes the coding more organized – We all know that a Clean Program is a Clean Coding. Using OOP instead of procedural makes things more organized and systematized (obviously).
It helps your team to work with each other easily – I know some of you had/have experienced team projects and some of you guys know that it’s important to have the same method, implementations, algorithm etc etc etc
It depends by the problem: the OOP paradigm is useful in designing distribuited systems or framework with a lot of entity living during the actions of the user (example: web application).
But if you have a math problem you will prefer a functional language (LISP); for a performance-critical systems you will use ADA or C, etc etc.
The language OOP is useful because too it use probabily the garbage collector (automatic use of memory) in the run of program: you you program in C a lot of time you must debug and correct manually a problem of memory.
OOP is useful when you have things. A socket, a button, a file. If you end a class in er it is almost always a function that is pretending to be a class. TestRunner more than likely should be a function that runs tests(and probably named run tests).
Personally, I think OOP is practically a necessity for any large application. I can't imagine having a program over 100k lines of code without using OOP, it would be a maintenance and design nightmare.
I tell you when OOP is bad.
When the architect writes really complicated, non-documented OOP code. Leaves half way through the project. And many of his common code pieces he used across various project has missing code. Thank god for .NET Reflector.
And the organization was not running Visual Source Safe or Subversion.
And I'm sorry. 2 pages of code to login is rather ridiculous even if it is cutely OOPed....