Related
I have begun to do some research about Evolutionary Art algorithm. I read a lot of documents about it. But it seems not easy to understand.
The website http://picbreeder.com is a great example for this. But I don't need this in the beginning because it is too complex.
Where can I find some simple code about this in Java? I think read code could help me much.
Thanks!!!
"Evolutionary Design by Computers" By David Bentley (amazon) has a couple of chapters on evolutionary art. However i dont think it includes any code / pseudocode. The canonical GA should do all you need, however the termination condition could be tricky as art is a subjective subject. (Not objective and therefore enumerable)
Hope this helps...
It looks like the EJC library might help you out, and it looks like a number of open source projects/tools come up if you Google for "java evolutionary computing."
I don't know how simple it is, and believe me it needs to be cleaned up a bit, but I have something that might get you started at https://github.com/murmux/Evo/tree/master/assignment2c It doesn't deal with art, rather game theory, but you can use it under the terms of the GPLv3 if you'd like. That uses Genetic Programming... I have another example using a more vanilla EA I might put up later.
Instead of evolving programs to play "Iterated Prisoner's Dilemma," you would evolve programs to generate an art work. The fun part is coming up with a way to "score" an image for its fitness. (Although Picbreeder seems to skip scoring by having you pick the mating pool directly...)
Check this app: EvoPic, its An evolutionary picture creator that uses Steady-State Genetic Algorithm, to produce evolutionary pictures by drawing uni-code characters in a picture box.
Example:
As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance.
Closed 10 years ago.
I was talking with some of the mentors in a local robotics competition for 7th and 8th level kids. The robot was using PBASIC and the parallax Basic Stamp. One of the major issues was this was short term project that required building the robot, teaching them to program in PBASIC and having them program the robot. All in only 2 hours or so a week over a couple months. PBASIC is kinda nice in that it has built in features to do everything, but information overload is possible to due this.
My thought are simplicity is key.
When you have kids struggling to grasp:
if X>10 then <DOSOMETHING>
There is not much point in throwing "proper" object oriented programming at them.
What are the essentials needed to foster an interest in programming?
Edit:
I like the notion of interpreted on the PC as learning tool. Due to the target platforms more than likely being somewhat resource constrained, I would like to target languages that are appropriate for embedded work. (Python and even Lua require more resources than the target likely to have. And I actually kinda like Lua.) I suppose that is one of the few virtues BASIC has, it has been ran on systems with less than 4K for over 30 years. C may not be a bad option if there are some "friendly" tools available such as Ch.
The most important is not a lot of boiler plate to make the simplest program run.
If you start of with a bunch of
import Supercalifragilistic from <expialidocious>
public void inherited security model=<apartment>
public : main .....
And tell them they "not to worry they aren't supposed to understand that" - you are going to put off both the brightest and the dumbest.
The nice thing about python is that printing "hello world" is print "hello world"
Fun, quick results. Capture the attention span of the kid.
Interpretive shells like most scripting languages offer (command line) that lets the student just type 1 or 2 liners is a big deal.
python:
>>> 1+1
2
Boom, instant feedback, kid thinks "the computer is talking back". Kids love that. Remember Eliza, anyone?
If they get bogged down in installing an IDE, creating a project, bleh bleh bleh, sometimes the tangents will take you away from the main topic.
BASIC is good too.
Look for some things online like "SIMPLE" : http://www.simplecodeworks.com/website.html
A team of researchers, beginning at Rice, then spreading out to Brown, Chicago, Northeastern, Northwestern, and Utah, have been studying this question for about 15 years. I can't summarize all their discoveries here, but here are some of their most important findings:
Irregular syntax can be a barrier to entry.
The language should be divided into concentric subsets, and you should choose a subset appropriate to the student's level of knowledge. For example, their smallest subset is called the "Beginning Student" language.
The compiler's error messages should be matched to the students' level of knowledge. If you are using subsets, different subsets might give different messages for the same error.
Beginners find it difficult to learn the phase distinction: separate phases for type checking and run time, with different kinds of errors. For this reason, beginners do better with a language where types are checked at run time, i.e., a dynamically typed language.
Beginners find it difficult to reason about mutable variables and mutable objects. If you teach pure functional programming, by contrast, you can leverage students' experience with high-school and middle-school algebra.
Beginning students are more engaged by an interactive programming environment than by the old edit-compile-link-go model.
Beginning students are engaged by splash and by interactivity. It's good if your language's standard library provides built-in support for creating and displaying images. It's better if those images are supported within the interactive programming environment, instead of requiring a separate player or viewer. And it's even better if your standard library can support moving images, or some other kind of animation.
Interestingly, they have got very good results with just 2D images. Even though we are all surrounded by examples of 3D computer graphics, students seem to get very engaged working with just two-dimensional images.
These results have been obtained primarily with college students, and they have been replicated at over 20 universities. However, the research team has also done some work with high-school and middle-school students. The first papers on that work are just coming out, so I'm less aware of the new findings and am not able to summarize them.
When you have kids struggling to grasp:
if X>10 then <DOSOMETHING>
Maybe it's a sign they shouldn't be doing programming?
What are the essentials needed to foster an interest in programming?
To see success with no or little effort. To create something running in a matter of minutes. A lot of programming languages can offer it, including the scary C++.
In order to avoid complication with #includes, multiple source files, modularization and compilation, why not have a look elsewhere? Try to write some Excel macros or use any other software with some basic built-in scripting language to automate certain tasks?
Another idea could be to play with web pages. It is not exactly programming, but at least easy to achieve something and show to others with pride.
This has been said on SO before, but... try Scratch. It's an incredible learning tool for kids. It teaches the basics of programming concepts in a hands-on and language-independent way. After a bit of playing around with it they can get down to learning a specific language's implementation of the concepts they already understand.
The common theme in languages that are easy for beginners - especially children to pick up is that there's very little barrier to entry, and immediate feedback. If "hello world" doesn't look a lot like print "Hello, world!", it's going to be harder for people to pick up. The following features along those lines come to mind:
Interpreted, or incrementally JIT compiled (which looks like an interpreter to the user)
No boilerplate
No attempt to enforce a specific programming style (e.g. Java requiring that everything be in a class definition, or Haskell enforcing purely functional design)
Dynamic typing
Implicit coercion (maybe)
A REPL
Breaking the problem (read program) down into a small set of sections (modules) that do one thing and do it very well.
You have to get them to stop thinking like a user and start thinking like a programmer. They need to take it one step at a time. Ask them what they have to think of in order to figure out the problem them selves and then write them down as steps. If you can then you break each step even more in the same mater. When done you will have the program in english making it simpler to program for real.
I did this with a friend that just could not get it and now he can. He used to look at something that I did and be bewildered and I would say that he has done more complex stuff than this.
One of the more persistently-present arguments I have had with other programmers is whether or not one's first language should require explicit type languages. Many are of the opinion that learning a language which requires you to explicitly declare type information is one which will teach you to program typefully. Conversely, it can be said that dynamic languages might present a less demanding learning curve. It goes either way, I suppose.
My advice: start with a simple model of how a computer works. I am particular to stack machines as good tools for teaching computation.
Remember that beginners are learning two disciplines at the same time: how computers work and the abstract logic involved (the basics of Computer Science), plus how to write programs that match their intended logic (learning a specific language's syntax and idioms). You have to address both concerns in an interwoven fashion in order for the students to quickly become effective. This is also the reason experienced programmers can often pick up new languages quickly.
It's worth noting Python grew out of a project for a language named ABC, which was targeted at beginners. For example, the required colon isn't strictly required, but was found to improve readability:
if some_condition:
do_this()
I got 3 words : Karel the Robot.
it's a really really simple 'language' that is designed to teach people the basis of programming :
Look for it on the web. You can look at this, though I never tried it :
http://karel.sourceforge.net/
While this isn't related to programming a robot, I think web programming is a great place to start with kids that age. It's how I started at that exact age. It easily translates to something kids understand if they use the web at all. Start with HTML, throw in Javascript, and soon they want to be doing features requiring server-side scripting or some sort, and things progress from there.
With the kind of kids who are already interested in robotics, though, I'd actually go for a different language like the ones already described. If you want to work in a field like robotics, you don't need to be convinced to try something hard. You need to be challenged.
A few years ago I saw a presentation at Ignite! Seattle from one of the people working on the project now known as Kodu who envisioned as a programming language for children. He spent time talking about what common language features could simply be thrown out in a programming environment meant to teach fundamentals.
A lot of cherished imperative constructs, like C-style for loops, were simply left out in favor of a simple object-messaging approach. Object-oriented programming isn't hard to understand when you think about "objects" and "messages"; the hard part is when you deal with things that programmers, but not children, care about, like inheritance and contracts and sweeping abstractions. I've got this thing (noun), now act on it (verb), in this way (adverb like quickly), when thing (sees/bumps into) something (with some attribute) (that's your if). Events are really conditions, and have all of the power of conditions, but it's up to the runtime to identify when those events happen.
This kind of event and messaging driven approach probably translates even better to robots than procedural programming would, anyway, so it might be a good way to look at the problem. Try not to think about what you'd "need" to know to program in C or Pascal or something; think about what you'd want to be able to make something do.
I have wonder that many big applications (e.g. social websites such as facebook) are build with many languages into its platform.
They usually start with AJAX browser support, then scale down to PHP scripting, then move towards a powrful OOP technologie such as Java or .NET, and finally a primitive language to increase performance in crucial operations such as C.
My question is how should I determinate the edge of the layers between languages. When PHP, when Java, when C and so on. And the other question is if should those languages integrate in a vertcal fashion for simplicity and maintanance, or could it be cases when you decide to program on module of your app in Java and the other in native C.
What are the context variables that push me to move to a better performance language? (e.g. concurrency issues due increase of users)
Don't tell me that PHP overlaps .NET and Java Technologies. In a starter point it does, but when the network is overload you start seeing the diferences. I mean how can I achieve Multithreading in PHP as in Java with the same performance. The thing it's hard to answer my wuestion is becasue there is not so much reading about this. You maybe find some good books covering PHP, but few telling how when and why integrate different languages.
Each language was created for different purposes, Python is strong with string operations, Perl very powerful in batch scripting, PHP a very reliable application web server, C the mother of most popular languages.
Best,
Demian.
On one end of the scale, you move to a higher performance language whenever your profiling and measurements tell you that you have a bottleneck that can't be fixed with better algorithms, data structures, or other optimisation.
At the other end, you move to a higher level language (ie. more abstraction, better libraries) whenever your management allow you to do so. ;)
I believe most teams simply use what they are best familiar with.
There are also questions of licensing that can influence the decision.
That is, if you're talking about technologies that compare to each other and solve the problem on the same level (for example ASP.NET/JSF/JSP/PHP...). But you can't compare .NET with C++ for example, they are meant to solve different problems on different abstraction levels.
My criterion for any programming language is "does it help me to get the job done or does it just get in the way?" If the latter, then it's time to move on.
From an economical point of view the answer is easy: on a regular basis just look what will be cheaper. Either continue with the current technology and maybe stretch the envelope a bit more. Or switch to something new. When you compare the two alternatives the cost of the investment already done is not important anymore since you've already spent that money/effort. You only have to look ahead: cost of licenses, education, etc.
Of course this is easier said then done, but just sitting down with a few people, thinking about it, and maybe try to come up with some numbers already helps a lot. I have seen too many projects that continued with technology that really wasn't suited for the job anymore.
Also hard numbers don't tell the whole story. There will be resistance because of unfamiliar technology, experts who are losing their status, etc.
Identify the bottleneck
Solve bottleneck
Go to 1
I'm sure you can imagine that step 2 is the one where decisions like "What programming language do we use" and "where do we put the coffee machine" come into play. That's the basic rule.
[Edit:] Earlier I asked this as a perhaps poorly-framed question about when to use OOP versus when to use procedural programming - some responses implied I was asking for help understanding OOP. On the contrary, I have used OOP a lot but want to know when to use a procedural approach. Judging by the responses, I take it that there is a fairly strong consensus that OOP is usually a better all-round approach but that a procedural language should be used if the OOP architecture will not provide any reuse benefits in the long term.
However my experience as a Java programmer has been otherwise. I saw a massive Java program that I architected rewritten by a Perl guru in 1/10 of the code that I had written and seemingly just as robust as my model of OOP perfection. My architecture saw a significant amount of reuse and yet a more concise procedural approach had produced a superior solution.
So, at the risk of repeating myself, I'm wondering in what situations should I choose a procedural over an object-oriented approach. How would you identify in advance a situation in which an OOP architecture is likely to be overkill and a procedural approach more concise and efficient.
Can anyone suggest examples of what those scenarios would look like?
What is a good way to identify in advance a project that would be better served by a procedural programming approach?
I like Glass' rules of 3 when it comes to Reuse (which seems to be what you're interested in).
1) It is 3 times as difficult to
build reusable components as single
use components 2) A reusable
component should be tried out in three
different applications before it will
be sufficiently general to accept into
a reuse library
From this I think you can extrapolate these corollaries
a) If you don't have the budget
for 3 times the time it would take you
to build a single use component, maybe
you should hold off on reuse. (Assuming Difficulty = Time)
b) If
you don't have 3 places where you'd
use the component you're building,
maybe you should hold off on building
the reusable component.
I still think OOP is useful for building the single use component, because you can always refactor it into something that is really reusable later on. (You can also refactor from PP to OOP but I think OOP comes with enough benefits regarding organization and encapsulation to start there)
Reusability (or lack of it) is not bound to any specific programming paradigm. Use object oriented, procedural, functional or any other programming as needed. Organization and reusability come from what you do, not from the tool.
Those who religiously support OOP don't have any facts to justify their support, as we see here in these comments as well. They are trained (or brain washed) in universities to use and praise OOP and OOP only and that is why they support it so blindly. Have they done any real work in PP at all? Other then protecting code from careless programmers in a team environment, OOP doesn't offer much. Personally working both in PP and OOP for years, I find that PP is simple, straight forward and more efficient, and I agree with the following wise men and women:
(Reference: http://en.wikipedia.org/wiki/Object-oriented_programming):
A number of well-known researchers and programmers have criticized OOP. Here is an incomplete list:
Luca Cardelli wrote a paper titled “Bad Engineering Properties of Object-Oriented Languages”.
Richard Stallman wrote in 1995, “Adding OOP to Emacs is not clearly an improvement; I used OOP when working on the Lisp Machine window systems, and I disagree with the usual view that it is a superior way to program.”
A study by Potok et al. has shown no significant difference in productivity between OOP and procedural approaches.
Christopher J. Date stated that critical comparison of OOP to other technologies, relational in particular, is difficult because of lack of an agreed-upon and rigorous definition of OOP. A theoretical foundation on OOP is proposed which uses OOP as a kind of customizable type system to support RDBMS.
Alexander Stepanov suggested that OOP provides a mathematically-limited viewpoint and called it “almost as much of a hoax as Artificial Intelligence” (possibly referring to the Artificial Intelligence projects and marketing of the 1980s that are sometimes viewed as overzealous in retrospect).
Paul Graham has suggested that the purpose of OOP is to act as a “herding mechanism” which keeps mediocre programmers in mediocre organizations from “doing too much damage”. This is at the expense of slowing down productive programmers who know how to use more powerful and more compact techniques.
Joe Armstrong, the principal inventor of Erlang, is quoted as saying “The problem with object-oriented languages is they’ve got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle.”
Richard Mansfield, author and former editor of COMPUTE! magazine, states that “like countless other intellectual fads over the years (“relevance”, communism, “modernism”, and so on—history is littered with them), OOP will be with us until eventually reality asserts itself. But considering how OOP currently pervades both universities and workplaces, OOP may well prove to be a durable delusion. Entire generations of indoctrinated programmers continue to march out of the academy, committed to OOP and nothing but OOP for the rest of their lives.” and also is quoted as saying “OOP is to writing a program, what going through airport security is to flying”.
You gave the answer yourself - big projects simply need OOP to prevent getting too messy.
From my point of view, the biggest advantage of OOP is code organization. This includes the principles of DRY and encapsulation.
I would suggest using the most concise, standards-based approach that you can find for any given problem. Your colleague who used Perl demonstrated that a good developer who knows a particular tool well can achieve great results regardless of the methodology. Rather than compare your Java-versus-Perl projects as a good example of the procedural-versus-OOP debate, I would like to see a face-off between Perl and a similarly concise language such as Ruby, which happens to also have the benefits of object orientation. Now that's something I'd like to see. My guess is Ruby would come out on top but I'm not interested in provoking a language flame-war here - my point is only that you choose the appropriate tool for the job - whatever approach can accomplish the task in the most efficient and robust way possible. Java may be robust because of its object orientation but as you and your colleague and many others who are converting to dynamic languages such as Ruby and Python are finding these days, there are much more efficient solutions out there, whether procedural or OOP.
I think DRY principle (Don't Repeat Yourself) combined with a little Agile is a good approach. Build your program incrementally starting with the simplest thing that works then add features one by one and re-factor your code as necessary as you go along.
If you find yourself writing the same few lines of code again and again - maybe with different data - it's time to think about abstractions that can help separate the stuff that changes from the stuff that stays the same.
Create thorough unit tests for each iteration so that you can re-factor with confidence.
It's a mistake to spend too much time trying to anticipate which parts of your code need to be reusable. It will soon become apparent once the system starts to grow in size.
For larger projects with multiple concurrent development teams you need to have some kind of architectural plan to guide the development, but if you are working on your own or in small cooperative team then the architecture will emerge naturally if you stick to the DRY principle.
Another advantage of this approach is that whatever you do is based on real world experience. My favourite analogy - you have to play with the bricks before you can imagine how the building might be constructed.
I think you should use procedural style when you have a very well specified problem, the specification won't change and you want a very fast running program for it. In this case you may trade the maintainability for performance.
Usually this is the case when you write a game engine or a scientific simulation program. If your program calculate something more than million times per second it should be optimized to the edge.
You can use very efficient algorithms but it won't be fast enough until you optimize the cache usage. It can be a big performance boost your data is cached. This means the CPU don't need fetch bytes from the RAM, it know them. To achieve this you should try to store your data close to each other, your executable and data size should be minimal, and try using as less pointers as you can (use static global fixed sized arrays where you can afford).
If you use pointers you are continuously jumping in the memory and your CPU need to reload the cache every time. OOP code is full of pointers: every object is stored by its memory address. You call new everywhere which spread your objects all over the memory making the cache optimization almost impossible (unless you have an allocator or a garbage collector that keeps things close to each other). You call callbacks and virtual functions. The compiler usually can't inline the virtual functions and a virtual function call is relatively slow (jump to the VMT, get the address of the virtual function, call it [this involves pushing the parameters and local variables on the stack, executing the function then popping everything]). This matters a lot when you have a loop running from 0 to 1000000 25 times in every second. By using procedural style there aren't virtual function and the optimizar can inline everything in those hot loops.
If the project is so small that it would be contained within one class and is not going to be used for very long, I would consider using functions. Alternatively if the language you are using does not support OO (e.g. c).
"The problem with object-oriented languages is they’ve got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle.” —Joe Armstrong
Do you want the jungle?
I think the suitability of OOP depends more on the subject area you're working in than the size of the project. There are some subject areas (CAD, simulation modeling, etc.) where OOP maps naturally to the concepts involved. However, there are a lot of other domains where the mapping ends up being clumsy and incongruous. Many people using OOP for everything seem to spend a lot of time trying to pound square pegs into round holes.
OOP has it's place, but so do procedural programming, functional programming, etc. Look at the problem you're trying to solve, then choose a programming paradigm that allows you to write the simplest possible program to solve it.
Procedural programs can be simpler for a certain type of program. Typically, these are the short script-like programs.
Consider this scenario:
Your code is not OO. You have data structures and many functions throughout your progam that operate on the data structures. Each function takes a data structure as a parameter and does different things depending on a "data_type" field in the data structure.
IF all is working and not going to be changed, who cares if it's OO or not? It's working. It's done. If you can get to that point faster writing procedurally, then maybe that's the way to go.
But are you sure it's not going to be changed? Let's say you're likely to add new types of data structures. Each time you add a new data structure type that you want those functions to operate on, you have to make sure you find and modify every one of those functions to add a new "else if" case to check for and add the behavior you want to affect the new type of data structure. The pain of this increases as the program gets larger and more complicated. The more likely this is, the better off you would be going with the OO approach.
And - are you sure that it's working with no bugs? More involved switching logic creates more complexity in testing each unit of code. With polymorphic method calls, the language handles the switching logic for you and each method can be simpler and more straightforward to test.
The two concepts are not mutually exclusive, it is very likely that you will use PP in conjunction with OOP, I can't see how to segregate them.
I believe Grady Booch said once that you really start to benefit a lot from OOP at 10000+ lines of code.
However, I'd always go the OO-way. Even for 200 lines. It's a superior approach in a long term, and the overhead is just an overrated excuse. All the big things start small.
One of the goals of OOP was to make reusability easier however it is not the only purpose. The key to learning to use objects effectively is Design Patterns.
We are all used to the idea of algorithms which tell us how to combine different procedures and data structures to perform common tasks. Conversely look at Design Patterns by the Gang of Four for ideas on how to combine objects to perform common tasks.
Before I learned about Design Patterns I was pretty much in the dark about how to use objects effectively other than as a super type structure.
Remember that implementing Interfaces is just as important if not more important than inheritance. Back in the day C++ was leading example of object oriented programming and using interfaces are obscured compared to inheritance (virtual functions, etc). The C++ Legacy meant a lot more emphasis was placed on reusing behavior in the various tutorials and broad overviews. Since then Java, C#, and other languages have moved interface up to more a focus.
What interfaces are great for is precisely defining how two object interact with each. It is not about reusing behavior. As it turns out much of our software is about how the different parts interact. So using interface gives a lot more productivity gain than trying to make reusable components.
Remember that like many other programming ideas Objects are a tool. You will have to use your best judgment as to how well they work for your project. For my CAD/CAM software for metal cutting machines there are important math functions that are not placed in objects because there is no reason for them be in objects. Instead they are exposed from library and used by the object that need them. Then there is are some math function that were made object oriented as their structure naturally lead to this setup. (Taking a list of points and transforming it in on of several different types of cutting paths). Again use your best judgment.
Part of your answer depends on what language you're using. I know that in Python, it's pretty simple to move procedural code into a class, or a more formal object.
One of my heuristics is a based on how the "state" of the situation is. If the procedure pollutes the namespace, or could possibly affect the global state (in a bad, or unpredictable way), then encapsulating that function in an object or class is probably wise.
My two cents...
Advantages of procedural programming
Simple designing (fast proof of concept, battle with dramatically
dynamic requirements)
Simple inter-project communications
Natural when temporal order matters
Less overhead at runtime
The more Procedural code become good the closer it's to Functional. And advantages of FP are well known.
I always begin designing in a top-down fashion and in the top parts it's much easier to think in OOP terms. But when comes the time to code some little specific parts you are much more productive with just procedure programming.
OOP is cool in designing and in shaping the project, so that the divide-et-impera paradigm can be applied. But you cannot apply it in every aspect of your code, as it were a religion :)
If you "think OO" when you're programming, then I'm not sure it makes sense to ask "when should I revert to procedural programming?" This is equivalent to asking java programmers what they can't do as well because java requires classes. (Ditto .NET languages).
If you have to make an effort to get past thinking procedurally, then I'd advise asking about how you can overcome that (if you care to); otherwise stay with procedural. If it's that much effort to get into OOP-mode, your OOP code probably won't work very well anyway (until you get further along the learning curve.)
IMHO, the long term benefits of OOP outweigh the time saved in the short term.
Like AZ said, using OOP in a procedural fashion (which I do quite a bit), is a good way to go (for smaller projects). The bigger the project, the more OOP you should employ.
You can write bad software in both concepts. Still, complex software are much easier to write, understand and maintain in OO languages than in procedural. I wrote highly complex ERP applications in procedural language (Oracle PL/SQL) and then switched to OOP (C#). It was and still is a breath of fresh air.
To this point, the arguments of using OO for DRY and encapsulation is just adding unnecessary complexity in terms of how implicit it is and just sheer of how many layers that a class can inherit a lot of properties and methods into it.
not to mention that it's really hard to design a good OO cause you'd end up adding unrelated/unnecessary things that are going to be inherited throughout the whole layers of classes that inherits them. which is really bad if one parent class gets messy, the whole codebase is messy. and gets refactored.
also the fact that those inherited properties are not specifically fit into the use case to the class that inherits it which requires to be overridden. and to the ones that don't need them at all just have them for no good reason.
for something that does not need to be shared, sure there's abstract properties. but you'd end up having to implement them in all the instances that tries to inherits them.
this inheritance is just too magicky and gets dangerous.
but I'd give OO credit on how it's good at enforcing of what should be available. but then again it's too much power that is really easy to be wrongly used.
In my opinion, final class should be the default. and you need to deliberately choose if you want to allow it to inheritance.
Most studies have found that OO code is more concise than procedural code. If you look at projects that re-wrote existing C code in C++ (not something I necessarily advise, BTW) , you normally see reductions in code size of between 50 and 75 percent.
So the answer is - always use OO!
I've been studying OOP for quite a while now and I have a good grasp of the theory. I read the Head First book on OOP and, while it reinforced a lot of the theory, I found the case studies to be somewhat trivial.
I find that I'm applying OOP principles to my code each day, but I'm not sure if I'm applying them correctly. I need to get to the point where I am able to look at my code and know whether I'm using inheritance appropriately, whether my object is cohesive enough, etc.
Does anyone have any good recommendations (books, online guides, blogs, walk-throughs, etc.) for taking the next step in developing solid OOP skills?
I am working primarily in .NET (visual basic), but I welcome suggestions that incorporate various platforms.
Read Refactoring by Martin Fowler, and apply it to your own work.
It will take you through a litany of malodorous characteristics of software code that describe how to detect improperly constructed classes, and even more importantly, how to fix them.
Consider looking into Design Patterns. Although it seems like they aren't commonly used in enterprise applications (I've seen them more commonly used in API's and Frameworks than embedded into enterprise code), they could be applied to make software simpler or more robust in a lot of situations if only developers knew how to apply them.
The key is to understand the design patterns first, then with experience you'll learn how to apply them.
There is a Head First book on design patterns that teaches the concept pretty simply, although if you want a book that really covers design patterns in detail, check out the Gang of Four design patterns book, which is basically what made design patterns mainstream and is referred to almost every time the topic is brought up.
Design patterns can be applied in pretty much any object-oriented language to some degree or another, although some patterns can be overkill or over engineering in some cases.
EDIT:
I also want to add, you should check out the book Code Complete 2. It's a very influential book in the world of software development. It covers a lot of different concepts and theories. I learn something new every time I read it. It's such a good book that if I read it every 6 months to a year, I look at it from a different perspective that makes me a better programmer just by re-reading it. No matter how much you might think you know, this book will make you realize just how little you really know. It's really a great book. I can't stress how much you should own this book.
If you already have the basics, I believe only experience will get you further. You say you are not sure if you are applying the principles correctly, but there is no one correct way. Code you write today, you'll look at in 6 months time, and wonder why you wrote it that way, and probably know of a better, cleaner way of doing it. I also guarantee that after 10 years, you'll still be learning new techniques and tricks. Don't worry too much about it, it will come, just read as much as you can, and try and apply what you read in small chunks.
I am currently half-way through the following book:
http://www.amazon.com/Applying-UML-Patterns-Introduction-Object-Oriented/dp/0131489062
I cannot recommend this book strongly enough in terms of learning a real-life, professional-grade, practical approach to drafting and applying a well-formed and iterative design strategy before diving into code.
I, too, read the "Head First" book and felt that I was much better off for having read it.
After having a few years of working-world experience, I now view the Craig Larman book that I am recommending to be a perfect "next step" for me.
About the Presence of "UML" in this Book Title:
Whether you have positive feelings or negative feelings about UML notation, please do not let that influence your decision to buy the book (ISBN 0131489062) in either direction.
The prominence of "UML" in the title is misleading. While the author does use and explain UML notation, these explanations are extremely well-woven into relevant design discussions, and at no time does this book read like a boring UML spec.
In fact, here is a quote taken directly from the book:
What's important is knowing how to think and design in objects, which is a very different and much more valuable skill than knowing UML notation. While drawing a diagram, we need to answer key questions: What are the responsibilities of the object? Who does it collaborate with? What design patterns should be applied? Far more important than knowing the difference between UML 1.4 and 2.0 !
This book at times seems like it is "speaking to" a lead architect or a project manager. What I mean to say by that is that it assumes that the reader has significant control over the planning and direction of a software project.
Nonetheless, even if you are only responsible for some very small piece of your company's projects and products, I would still recommend this book and encourage you to apply some "scaled down" modifications of the book's advice to your piece of the project.
My OOP epiphany came from Grady Booch's book, way long time ago. Suddenly I realized why objects were good.
While polymorphism is cool, encapsulation is 75% of why objects are cool. It is sort of like an interface: you see the buttons but not the wiring. Before objects, only the most disciplined coders kept their grubby fingers off the internal bits of other people's procedures (it was called "structured programming").
Object make it easy to Do the Right Thing. Inheritance and polymorphism are little bonuses.
One way to learn about objects is to read other peoples' code. I learned a lot by reading the source code for the Delphi VCL framework. Even just looking at the documentation for Java will help you see what a single object class should do and how it is designed to be used by other objects.
Start a project of your own and pay attention when you want to sub-class your own classes and find that you have to go back and break up some protected methods so you can override just one piece of a process instead of replacing all of it. See how ancestors talk to descendants by calling abstract functions. In other words, go make a lot of mistakes and learn from them.
Enjoy!
Frankly, re-reading old David Parnas papers on information hiding helps me get in the right state of mind. The case studies may not be directly applicable but you should be able to get some useful generalizations out of them.
My epiphany happened when I tried to implement a very OO problem (dynamically and recursively building SQL statements) in VB6. The best way to understand polymorphism or inheritance is to need it and not be able to use it.
One thing that will definitely help you is working on a well-known, respected open source project. Either dig through the source code and see how things are done or try to make some additions / modifications. You'll find that there isn't one style or one right answer for most problems, but by looking at several projects, you'll be able to get a wide view of how things can be done. From there, you'll begin to develop your own style and will hopefully make some contributions to open source in the process.
I think you have to attempt and fail at implementing OO solutions. That's how I did it anyway. What I mean by fail is that you end up writing smelly code while successfully delivering a working solution. After it's written you'll get a feel for where things didn't quite feel right. You may have some epiphanies, and/or you may go and hunt for a slicker solution from other programmers. Undoubtedly you'll implement some variation of standard design patterns by accident. In hindsight, a light will click on (oh! so that's what a visitor is for), and then understanding will accelerate.
As others have said, I think tooling through some good OO open source code is a good idea. So is working with more experienced programmers who would be willing to critique your work. However understanding comes through doing.
You might want to try to read (and write) some Smalltalk for a while. Squeak is a free implementation that can show you the power of a fully object-oriented environment (unlike java or .net). All library code source is included. The language itself is incredibly simple. You'll find that java and c# are slowly adding the features well-known to Smalltalk since 1980.
Tortoise HG is extrodanarily well designed piece of OO open source software (written in Python).
If you already understand the basics, building something from scratch in a fully object oriented language will be a good step in fully understanding OOP software architecture. If you don't know Python, Python Essential Reference will take you through the language in full in a few days to a week.
After you understand the language take a look through the software above and you'll have all sorts of epiphanies.
To understand basically anything thoroughly, you need to have a decent knowledge of at least one abstraction level above and one level below it. In the case of OO, others have mentioned design patterns as the layer above OO. This helps a lot to illustrate why OO is useful.
As far as the layer below OO, try to play around with higher-order functions/late binding for a while and get a feel for how these relatively simple constructs are used. Also, try to understand how OO is implemented under the hood (vtables, etc.) and how it can be done in pure C. Once you grok the value of using higher order functions and late binding, you'll quickly realize that OO is just a convenient syntax for passing around a set of related functions and the data they operate on.