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I've recently forayed into the world of functional programming (FP) and am wondering how to "think functionally" for even moderately sized applications? Especially w.r.t. the analysis and design of FPs.
With OOP we're trained to think in terms of objects, their attributes and relations. We model our analyses/designs using class and sequence diagrams. However, the same models seem to be a bad fit when designing for FPs. What are the equivalent modeling paradigms for functional programming? It seems DFDs maybe a good fit but I maybe wrong.
For example: I was thinking of designing a simulation of Monopoly, the board game using Haskell, just to learn the language. When doing OOAD you come up with classes like board contains items that have attributes/methods attached to it. You have player and various other objects and their associated relations that can be captured in a class diagram. And their interactions in a sequence diagram. However, these modeling paradigms doesn't seem to transfer well for functional programs. So just "how" do you model functionally?
Note: I'm looking for concrete references/examples that can explain how to analyze and design functional programs given that I'm coming from a heavily object-oriented way of thinking/modeling.
According to Simon Peyton Jones:
The language in which you write profoundly affects the design of
programs written in that language. For example, in the OO world, many
people use UML to sketch a design. In Haskell or ML, one writes type
signatures instead. Much of the initial design phase of a functional
program consists of writing type definitions. Unlike UML, though, all
this design is incorporated in the final product, and is
machine-checked throughout.
Source: Masterminds of Programming
So instead of drawing all the fancy UML diagrams, you actually write type definitions coupled with undefined in the design phase.
All of my programming these days consists of single-person projects. If I were collaborating on a project with other programmers, I think that writing type definitions and using undefined would be a good approach.
But I gather what you're really looking for is some advice about how you can learn to think functionally. So here are some thoughts.
When programming in Haskell, there are two ways I think about the program I'm writing.
If the program is mathematical, I think of the program as a set of equations.
Otherwise, I tend to think of the program as one or more chains of of data transformations. (So perhaps DFDs would be useful.)
So in your Monopoly example, my first thought would be to figure out how I'm going to represent the state of the board (e.g., which properties have houses, who owns them). Then I might have a function that transforms the board when someone buys a property, and other functions for other things players might do. (There's also monads for representing state, State and StateT. I might use them, if and when I feel they will make the code clearer, but I usually keep things basic to start.)
One of the mistakes I made most often as a beginner was to create a lot of unnecessary classes and data types.
Short answer: composition of smaller programs.
You first study the problem before you, then you develop a set of small operations (often in the form of combinators) that you reckon make sense in that problem's context, and finally you build the solution around those operations. I'm under the impression that all packages found on Hackage follow this approach.
In this way the final solution is (more often than not) simple, clear and elegant. As you can appreciate the aforementioned set of small operations you choose for your solution is critical; with practice, you'll develop the sensibility to pick it wisely.
My book suggestion is Pearls of Functional Algorithm Design, by Richard Bird, Google Books (preview). In this book you'll learn about the calculational approach to functional programming, which I think is most valuable.
Two books you might be interested in:
Structure and Interpretation of Computer Programs - a classic intro to CS textbook in Scheme. I think it's a must for programmers interested in FP.
How to Design Programs - similar to SICP, slightly more modern and focuses on design. The language of choice here is Racket.
If you want a hands-on project in Haskell, I'd recommend Write Yourself a Scheme in 48 Hours, a wonderful tutorial for implementing an interpreter for Scheme. AST manipulation is where FP (and especially Haskell) shines, so I think writing an interpreter is a good experience for new FP programmers.
My perspective regarding the FP vs OO analysis and design debate is the following:
OOAD and DDD (Domain-Driven Design) are very useful tools for software systems decomposition;
FP has types, OO has classes and interfaces: they are dual in different worlds;
FP has type instances, OO has class instances (aka, objects in OO);
Use composition in FP, where in OO you would use inheritance;
Both FP and OO languages come with polymorphic constructs;
Both FP and OO use collections (sets, lists and maps) to make connections between instances (of types in FP, and of classes in OO);
Associations in FP are typically implemented as collections of instance IDs, whereas absensein OO they are implemented as collections of references to the memory locations of objects. This comes from the immutability property of data structures in FP.
Most books in FP, like those referred in the other answers before mine, do not show you how to design (aka, decompose) complex real-world problems. They generally demonstrate FP's features with very short examples (e.g., compare them with the examples in Craig Larman's Applying UML and Patterns excelent book, and judge yourself).
For something more close to what could be called Functional-Oriented Analysis and Design (FOAD), I recommend these:
Elixir in Action
Domain Modeling Made Functional: Tackle Software Complexity with Domain-Driven Design and F#
Functional and Reactive Domain Modeling
Functional Programming in Scala
DDD, OOAD, and FOAD, can be implemented in any programming language, however some programming languages offer constructs that make these approaches easier or harder to implement, but they are perfectly practical. This is evident by the many sources you can find discussing DDD in the context of FP.
Dr. Alan Kay said this regarding the essence of OOP (here):
OOP to me means only messaging, local retention and protection and
hiding of state-process, and extreme late-binding of all things. It
can be done in Smalltalk and in LISP. There are possibly other systems
in which this is possible, but I'm not aware of them.
Following this statement, Joe Armstrong, one of Erlang's creator, an FP language with important uses in the industry (e.g., WhatsApp), argues that Erlang is perhaps the most OO language around (see this interview also featuring Ralph Johnson).
Also, some say that Erlang is the best language that captured the essence of OO programming: the passing of messages between objects.
Hope this was helpful.
I can only speak from the perspective of Erlang OTP. We think in terms of processes, which have a state and functions. So in the state the process will have all the "variables" and handler functions react to data the process receives in its message queue. They act on the received data, possibly alter their own state, possibly return some data and/or have some side effects. The state can be stored in a map or a record or any other valid data type. Usually we define a record called state() or loopData().
I read a debate in the comments here (current live site, without comments).
Why the debate? A Dataset for me is like a relational database, an Object is a hierarchical-like model. Why do people absolutely want a "pure" Object model, whereas we still deal with relational databases, so why not combine the two?
And if we should, is there any lightweight, comprehensive framework that allows us to do that (not a heavy mammoth, like NHibernate, which has a huge learning curve)?
"Pure objects" are a lot easier to work with, the typed object gives you intellisense and compile-time type checking.
Bare datasets are very cumbersome and annoying to work with - you need to know the column names, there's no type checking possible, so if you mistype a column name, you're out of luck and won't discover the error until runtime (the worst possible scenario).
Typed datasets are a step in the right direction, but the "things" you work with in your .NET code are still tied very closely and tightly to your database implementation - not typically a good thing, since any change in the underlying database might affect your app all the way up to your UI and cause a lot of changes being necessary.
Using an ORM like NHibernate allows you to better abstract and decouple the database (physical storage) layer from your logical business model - only in the simplest of scenarios will those two be an exact 1:1 match, so you'll need some kind of "translation" or mapping between the two anyway.
So all in all - using typed datasets might be okay for small, simple apps, but for a challenging, larger-scale, enterprise-level business app, I would never recommend coupling your business object model so closely and tightly to the database.
Marc
why do people absolutly want "pure" Object model
Because you don't want your application to depend on the database schema
Well, all the reasons you give were the same as the academical reasons that were given for EJB in Java which was a mess in the past. So arent't people falling into another fashionable hype ?
As I read here:
http://blogs.tedneward.com/2006/06/26/The+Vietnam+Of+Computer+Science.aspx
the promise is one thing, the reality is other thing.
Where is the proof upon the claims ?
Scientifically, Complexity is tight to the Concept of Entropy, you cannot reduce the inherent complexity of things, you can just move it somewhere else, so for me there is something fundamentally irational.
Ted Newards is highly controversial because it seems to me that everybody is herding like in the old EJB days: nobody dared to say EJB suck until Rod Johnson gets out with Hibernate.
Now it seems nobody cares to say ORM frameworks like Hibernate, Entity Framework, etc. are too complex, because there isn't yet another Rod Johnson II maybe :)
You pretend that adding a new layer solves the problem, it's not always the case even theorcially, like adding more team members when a project becomes a mess because adding more programmers also mean add to coordination and communication problem.
And in practice, what it seems, is that the layers that should be independant at least from the GUI viewpoint, aren't really. I see many people struggle to do simple stuff in the GUI when they use an ORM.
From what I understand, OOP is the most commonly used paradigm for large scale projects. I also know that some smaller subsets of big systems use other paradigms (e.g. SQL, which is declarative), and I also realize that at lower levels of computing OOP isn't really feasible. But it seems to me that usually the pieces of higher level solutions are almost always put together in a OOP fashion.
Are there any scenarios where a truly non-OOP paradigm is actually a better choice for a largescale solution? Or is that unheard of these days?
I've wondered this ever since I've started studying CS; it's easy to get the feeling that OOP is some nirvana of programming that will never be surpassed.
In my opinion, the reason OOP is used so widely isn't so much that it's the right tool for the job. I think it's more that a solution can be described to the customer in a way that they understand.
A CAR is a VEHICLE that has an ENGINE. That's programming and real world all in one!
It's hard to comprehend anything that can fit the programming and real world quite so elegantly.
Linux is a large-scale project that's very much not OOP. And it wouldn't have a lot to gain from it either.
I think OOP has a good ring to it, because it has associated itself with good programming practices like encapsulation, data hiding, code reuse, modularity et.c. But these virtues are by no means unique to OOP.
You might have a look at Erlang, written by Joe Armstrong.
Wikipedia:
"Erlang is a general-purpose
concurrent programming language and
runtime system. The sequential subset
of Erlang is a functional language,
with strict evaluation, single
assignment, and dynamic typing."
Joe Armstrong:
“Because 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.”
The promise of OOP was code reuse and easier maintenance. I am not sure it delivered. I see things such as dot net as being much the same as the C libraries we used to get fro various vendors. You can call that code reuse if you want. As for maintenance bad code is bad code. OOP did not help.
I'm the biggest fan of OOP, and I practice OOP every day.
It's the most natural way to write code, because it resembles the real life.
Though, I realize that the OOP's virtualization might cause performance issues.
Of course that depends on your design, the language and the platform you chose (systems written in Garbage collection based languages such as Java or C# might perform worse than systems which were written in C++ for example).
I guess in Real-time systems, procedural programming may be more appropriate.
Note that not all projects that claim to be OOP are in fact OOP. Sometimes the majority of the code is procedural, or the data model is anemic, and so on...
Zyx, you wrote, "Most of the systems use relational databases ..."
I'm afraid there's no such thing. The relational model will be 40 years old next year and has still never been implemented. I think you mean, "SQL databases." You should read anything by Fabian Pascal to understand the difference between a relational dbms and an SQL dbms.
" ... the relational model is usually chosen due to its popularity,"
True, it's popular.
" ... availability of tools,"
Alas without the main tool necessary: an implementation of the relational model.
" support,"
Yup, the relational model has fine support, I'm sure, but it's entirely unsupported by a dbms implementation.
" and the fact that the relational model is in fact a mathematical concept,"
Yes, it's a mathematical concept, but, not being implemented, it's largely restricted to the ivory towers. String theory is also a mathematical concept but I wouldn't implement a system with it.
In fact, despite it's being a methematical concept, it is certainly not a science (as in computer science) because it lacks the first requirement of any science: that it is falsifiable: there's no implementation of a relational dbms against which we can check its claims.
It's pure snake oil.
" ... contrary to OOP."
And contrary to OOP, the relational model has never been implemented.
Buy a book on SQL and get productive.
Leave the relational model to unproductive theorists.
See this and this. Apparently you can use C# with five different programming paradigms, C++ with three, etc.
Software construction is not akin to Fundamental Physics. Physics strive to describe reality using paradigms which may be challenged by new experimental data and/or theories. Physics is a science which searches for a "truth", in a way that Software construction doesn't.
Software construction is a business. You need to be productive, i.e. to achieve some goals for which someone will pay money. Paradigms are used because they are useful to produce software effectively. You don't need everyone to agree. If I do OOP and it's working well for me, I don't care if a "new" paradigm would potentially be 20% more useful to me if I had the time and money to learn it and later rethink the whole software structure I'm working in and redesign it from scratch.
Also, you may be using another paradigm and I'll still be happy, in the same way that I can make money running a Japanese food restaurant and you can make money with a Mexican food restaurant next door. I don't need to discuss with you whether Japanese food is better than Mexican food.
I doubt OOP is going away any time soon, it just fits our problems and mental models far too well.
What we're starting to see though is multi-paradigm approaches, with declarative and functional ideas being incorporated into object oriented designs. Most of the newer JVM languages are a good example of this (JavaFX, Scala, Clojure, etc.) as well as LINQ and F# on the .net platform.
It's important to note that I'm not talking about replacing OO here, but about complementing it.
JavaFX has shown that a declarative
solution goes beyond SQL and XSLT,
and can also be used for binding
properties and events between visual
components in a GUI
For fault tolerant and highly
concurrent systems, functional
programming is a very good fit,
as demonstrated by the Ericsson
AXD301 (programmed using Erlang)
So... as concurrency becomes more important and FP becomes more popular, I imagine that languages not supporting this paradigm will suffer. This includes many that are currently popular such as C++, Java and Ruby, though JavaScript should cope very nicely.
Using OOP makes the code easier to manage (as in modify/update/add new features) and understand. This is especially true with bigger projects. Because modules/objects encapsulate their data and operations on that data it is easier to comprehend the functionality and the big picture.
The benefit of OOP is that it is easier to discuss (with other developers/management/customer) a LogManager or OrderManager, each of which encompass specific functionality, then describing 'a group of methods that dump the data in file' and 'the methods that keep track of order details'.
So I guess OOP is helpful especially with big projects but there are always new concepts turning up so keep on lookout for new stuff in the future, evaluate and keep what is useful.
People like to think of various things as "objects" and classify them, so no doubt that OOP is so popular. However, there are some areas where OOP has not gained a bigger popularity. Most of the systems use relational databases rather than objective. Even if the second ones hold some notable records and are better for some types of tasks, the relational model is unsually chosen due to its popularity, availability of tools, support and the fact that the relational model is in fact a mathematical concept, contrary to OOP.
Another area where I have never seen OOP is the software building process. All the configuration and make scripts are procedural, partially because of the lack of the support for OOP in shell languages, partially because OOP is too complex for such tasks.
Slightly controversial opinion from me but I don't find OOP, at least of a kind that is popularly applied now, to be that helpful in producing the largest scale software in my particular domain (VFX, which is somewhat similar in scene organization and application state as games). I find it very useful on a medium to smaller scale. I have to be a bit careful here since I've invited some mobs in the past, but I should qualify that this is in my narrow experience in my particular type of domain.
The difficulty I've often found is that if you have all these small concrete objects encapsulating data, they now want to all talk to each other. The interactions between them can get extremely complex, like so (except much, much more complex in a real application spanning thousands of objects):
And this is not a dependency graph directly related to coupling so much as an "interaction graph". There could be abstractions to decouple these concrete objects from each other. Foo might not talk to Bar directly. It might instead talk to it through IBar or something of this sort. This graph would still connect Foo to Bar since, albeit being decoupled, they still talk to each other.
And all this communication between small and medium-sized objects which make up their own little ecosystem, if applied to the entire scale of a large codebase in my domain, can become extremely difficult to maintain. And it becomes so difficult to maintain because it's hard to reason about what happens with all these interactions between objects with respect to things like side effects.
Instead what I've found useful is to organize the overall codebase into completely independent, hefty subsystems that access a central "database". Each subsystem then inputs and outputs data. Some other subsystems might access the same data, but without any one system directly talking to each other.
... or this:
... and each individual system no longer attempts to encapsulate state. It doesn't try to become its own ecosystem. It instead reads and writes data in the central database.
Of course in the implementation of each subsystem, they might use a number of objects to help implement them. And that's where I find OOP very useful is in the implementation of these subsystems. But each of these subsystems constitutes a relatively medium to small-scale project, not too large, and it's at that medium to smaller scale that I find OOP very useful.
"Assembly-Line Programming" With Minimum Knowledge
This allows each subsystem to just focus on doing its thing with almost no knowledge of what's going on in the outside world. A developer focusing on physics can just sit down with the physics subsystem and know little about how the software works except that there's a central database from which he can retrieve things like motion components (just data) and transform them by applying physics to that data. And that makes his job very simple and makes it so he can do what he does best with the minimum knowledge of how everything else works. Input central data and output central data: that's all each subsystem has to do correctly for everything else to work. It's the closest thing I've found in my field to "assembly line programming" where each developer can do his thing with minimum knowledge about how the overall system works.
Testing is still also quite simple because of the narrow focus of each subsystem. We're no longer mocking concrete objects with dependency injection so much as generating a minimum amount of data relevant to a particular system and testing whether the particular system provides the correct output for a given input. With so few systems to test (just dozens can make up a complex software), it also reduces the number of tests required substantially.
Breaking Encapsulation
The system then turns into a rather flat pipeline transforming central application state through independent subsystems that are practically oblivious to each other's existence. One might sometimes push a central event to the database which another system processes, but that other system is still oblivious about where that event came from. I've found this is the key to tackling complexity at least in my domain, and it is effectively through an entity-component system.
Yet it resembles something closer to procedural or functional programming at the broad scale to decouple all these subsystems and let them work with minimal knowledge of the outside world since we're breaking encapsulation in order to achieve this and avoid requiring the systems to talk to each other. When you zoom in, then you might find your share of objects being used to implement any one of these subsystems, but at the broadest scale, the systems resembles something other than OOP.
Global Data
I have to admit that I was very hesitant about applying ECS at first to an architectural design in my domain since, first, it hadn't been done before to my knowledge in popular commercial competitors (3DS Max, SoftImage, etc), and second, it looks like a whole bunch of globally-accessible data.
I've found, however, that this is not a big problem. We can still very effectively maintain invariants, perhaps even better than before. The reason is due to the way the ECS organizes everything into systems and components. You can rest assured that an audio system won't try to mutate a motion component, e.g., not even under the hackiest of situations. Even with a poorly-coordinated team, it's very improbable that the ECS will degrade into something where you can no longer reason about which systems access which component, since it's rather obvious on paper and there are virtually no reasons whatsoever for a certain system to access an inappropriate component.
To the contrary it often removed many of the former temptations for hacky things with the data wide open since a lot of the hacky things done in our former codebase under loose coordination and crunch time was done in hasty attempts to x-ray abstractions and try to access the internals of the ecosystems of objects. The abstractions started to become leaky as a result of people, in a hurry, trying to just get and do things with the data they wanted to access. They were basically jumping through hoops trying to just access data which lead to interface designs degrading quickly.
There is something vaguely resembling encapsulation still just due to the way the system is organized since there's often only one system modifying a particular type of components (two in some exceptional cases). But they don't own that data, they don't provide functions to retrieve that data. The systems don't talk to each other. They all operate through the central ECS database (which is the only dependency that has to be injected into all these systems).
Flexibility and Extensibility
This is already widely-discussed in external resources about entity-component systems but they are extremely flexible at adapting to radically new design ideas
in hindsight, even concept-breaking ones like a suggestion for a creature which is a mammal, insect, and plant that sprouts leaves under sunlight all at once.
One of the reasons is because there are no central abstractions to break. You introduce some new components if you need more data for this or just create an entity which strings together the components required for a plant, mammal, and insect. The systems designed to process insect, mammal, and plant components then automatically pick it up and you might get the behavior you want without changing anything besides adding a line of code to instantiate an entity with a new combo of components. When you need whole new functionality, you just add a new system or modify an existing one.
What I haven't found discussed so much elsewhere is how much this eases maintenance even in scenarios when there are no concept-breaking design changes that we failed to anticipate. Even ignoring the flexibility of the ECS, it can really simplify things when your codebase reaches a certain scale.
Turning Objects Into Data
In a previous OOP-heavy codebase where I saw the difficulty of maintaining a codebase closer to the first graph above, the amount of code required exploded because the analogical Car in this diagram:
... had to be built as a completely separate subtype (class) implementing multiple interfaces. So we had an explosive number of objects in the system: a separate object for point lights from directional lights, a separate object for a fish eye camera from another, etc. We had thousands of objects implementing a few dozen abstract interfaces in endless combinations.
When I compared it to ECS, that required only hundreds and we were able to do the exact same things before using a small fraction of the code, because that turned the analogical Car entity into something that no longer requires its class. It turns into a simple collection of component data as a generalized instance of just one Entity type.
OOP Alternatives
So there are cases like this where OOP applied in excess at the broadest level of the design can start to really degrade maintainability. At the broadest birds-eye view of your system, it can help to flatten it and not try to model it so "deep" with objects interacting with objects interacting with objects, however abstractly.
Comparing the two systems I worked on in the past and now, the new one has more features but takes hundreds of thousands of LOC. The former required over 20 million LOC. Of course it's not the fairest comparison since the former one had a huge legacy, but if you take a slice of the two systems which are functionally quite equal without the legacy baggage (at least about as close to equal as we might get), the ECS takes a small fraction of the code to do the same thing, and partly because it dramatically reduces the number of classes there are in the system by turning them into collections (entities) of raw data (components) with hefty systems to process them instead of a boatload of small/medium objects.
Are there any scenarios where a truly non-OOP paradigm is actually a
better choice for a largescale solution? Or is that unheard of these
days?
It's far from unheard of. The system I'm describing above, for example, is widely used in games. It's quite rare in my field (most of the architectures in my field are COM-like with pure interfaces, and that's the type of architecture I worked on in the past), but I've found that peering over at what gamers are doing when designing an architecture made a world of difference in being able to create something that still remains very comprehensible at it grows and grows.
That said, some people consider ECS to be a type of object-oriented programming on its own. If so, it doesn't resemble OOP of a kind most of us would think of, since data (components and entities to compose them) and functionality (systems) are separated. It requires abandoning encapsulation at the broad system level which is often considered one of the most fundamental aspects of OOP.
High-Level Coding
But it seems to me that usually the pieces of higher level solutions
are almost always put together in a OOP fashion.
If you can piece together an application with very high-level code, then it tends to be rather small or medium in scale as far as the code your team has to maintain and can probably be assembled very effectively using OOP.
In my field in VFX, we often have to do things that are relatively low-level like raytracing, image processing, mesh processing, fluid dynamics, etc, and can't just piece these together from third party products since we're actually competing more in terms of what we can do at the low-level (users get more excited about cutting-edge, competitive production rendering improvements than, say, a nicer GUI). So there can be lots and lots of code ranging from very low-level shuffling of bits and bytes to very high-level code that scripters write through embedded scripting languages.
Interweb of Communication
But there comes a point with a large enough scale with any type of application, high-level or low-level or a combo, that revolves around a very complex central application state where I've found it no longer useful to try to encapsulate everything into objects. Doing so tends to multiply complexity and the difficulty to reason about what goes on due to the multiplied amount of interaction that goes on between everything. It no longer becomes so easy to reason about thousands of ecosystems talking to each other if there isn't a breaking point at a large enough scale where we stop modeling each thing as encapsulated ecosystems that have to talk to each other. Even if each one is individually simple, everything taken in as a whole can start to more than overwhelm the mind, and we often have to take a whole lot of that in to make changes and add new features and debug things and so forth if you try to revolve the design of an entire large-scale system solely around OOP principles. It can help to break free of encapsulation at some scale for at least some domains.
At that point it's not necessarily so useful anymore to, say, have a physics system encapsulate its own data (otherwise many things could want to talk to it and retrieve that data as well as initialize it with the appropriate input data), and that's where I found this alternative through ECS so helpful, since it turns the analogical physics system, and all such hefty systems, into a "central database transformer" or a "central database reader which outputs something new" which can now be oblivious about each other. Each system then starts to resemble more like a process in a flat pipeline than an object which forms a node in a very complex graph of communication.
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.
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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....