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I have always wondered if I am thinking ahead too much or too little before I code something. This is especially true for me if I am not sure what possible future requirement changes I will be required to account for are. I don't know how flexible or abstracted I should make my classes. I'll give a quick example.
You want to write a program that plays blackjack against a computer and you're the type of person that likes to experiment. You begin to write the code for the deck, but then you realize blackjack could have 1, 2, 4, or any number of decks. You account for that, but then you realize that maybe the deck will be altered and not have any cards of value ten. You then decide that the deck should be completely versatile to allow any number of suits or ranks. You then decide that the rules for the deck should be able to be altered from the standard number of suits multiplied by the unique ranks to equal the total amount of cards in the deck... You can see where I am going here.
My question is this, are there any guidelines for how flexible a class should be?
Favor minimalism and encapsulation, avoiding functionalities you don't need.
It's of course good to design based on needs, but cluttering designs with things you do not use -- or could possibly use in the future -- should be minimized. It's fine to consider and implement what you are sure you will need.
When you understand and specify a 'future problem' (specifically, at that point in the future), you will often solve it different from today's solution.
Check out the great paper "On the Criteria to be Used in Decomposing Systems into Modules" by David Parnas, from back in 1972.
Generally speaking, you should try to identify areas of responsibility that can be pushed behind a very simple interface that hides useful functionality and complexity. You should strive to separate the what from the how in areas you feel are most likely to change (i.e. predicting variation).
Flexibility is indeed are a requirement for an application / system to be maintainable. Usually I find that a design following SOLID design principle, TDD and stateless business logic is easier to maintain.
Among all of SOLID principle, I find that [S]RP is the rule that makes the application maintainable. Following [S]RP, your system will be broken down to smaller pieces, with replaceable classes. Say that it can be broken to Deck, DeckRule, HitAction, etc.
Interface or inheritance will help, since you can easily swap your Deck with NoTenDeck or SpadeOnlyDeck. And you can swap the DeckRule to HardToWinDeckRule or ImpossibleWinDeckRule. With decorator or other design patterns such as composite will also help to make your system flexible. Don't forget Test Unit, it will help you to refactor the code.
And also sometimes you will need something like Breaking Change in which you need to tear down your current architecture and interfaces to be replaced with another design. Sometimes it is needed, but mostly not.
You can find several discussion at stackoverflow answer for DI vs Singleton and little about state or stateless.
I try to follow the agile principle of YAGNI ! - You Ain't Gonna Need It.
It isn't worth the effort of coming up with all these possible future requirements. There are an infinite number of possible future requirements. You can't account for all of them. Just do what you need to do to fulfill the requirements you already have.
If in the future you get new requirements, THEN change the system. (you do have good tests to make sure you don't break anything during refactoring right?)
Overall thoughts on flexibility
From your description of the problem I don't think your classes should be flexible as in "keep throwing every new aspect of the game rules into the same class". A class with too many responsibilities is fragile, hard to maintain and thus hard to change - ironically, treating a class as if it were flexible will eventually make it rigid ! Don't put all your eggs in one basket. Separate concern means separate class. Your overall design should be flexible, not so much your classes.
On the blackjack problem
Card games, especially complex and/or evolving ones, are generally most peculiar animals and thus probably not a good standard example to start experimenting with when trying to improve your design skills.
If you want real modularity, you'll probably need a pluggable rules engine that allows plugins to hook at different stages of a game, giving you access to relevant resources to alter anything from scores to the sequence of events in a turn to even other rules.
My take on this is
You already know your game will evolve in the future and you're going to need such an engine. To answer the "thinking ahead" part of your question, this means you'll start with a simple standard turn structure, a minimal rules engine and incrementally add to it as you implement each feature in your backlog. The thinking ahead you shouldn't do is trying to forecast every little detail in the engine upfront. In other words you'll use YAGNI as in "I ain't gonna need this rule/type of hook into the game" rather than "I ain't gonna need a rules engine" since you know you've got to have one anyway.
Or,
It's going to be, at least at first, a one-shot fixed-rules game. You'll need less raw flexibility in the game system here. Concentrate on use cases and try to make acceptance tests pass with the simplest possible technical solution. Take one little step at a time. Implement a working solution for just 1 deck with simple rules at first, then expand to more complex areas. This hopefully will lead you to a no-nonsense, well-designed system which may or may not involve some kind of rules engine.
You might also want to have a look at https://gamedev.stackexchange.com/ for game-specific design guidelines.
When writing code I tend to look for things that may be obvious additions later on. "Obvious is probably a word to define though. :-) It means things that you are sure will be in a future release. Other than that, I try not to worry about it.
Let's say I've made a list of concepts I'll use to draw my Domain Model. Furthermore, I have a couple of Use Cases from which I did a couple of System Sequence Diagrams.
When drawing the Domain Model, I never know where to start from:
Designing the model as I believe the system to be. This is, if I am modelling a the human body, I start by adding the class concepts of Heart, Brain, Bowels, Stomach, Eyes, Head, etc.
Start by designing what the Use Cases need to get done. This is, if I have a Use Case which is about making the human body swallow something, I'd first draw the class concepts for Mouth, Throat, Stomatch, Bowels, etc.
The order in which I do things is irrelevant? I'd say probably it'd be best to try to design from the Use Case concepts, as they are generally what you want to work with, not other kind of concepts that although help describe the whole system well, much of the time might not even be needed for the current project. Is there any other approach that I am not taking in consideration here? How do you usually approach this?
Thanks
Whether DDD, or not, I would recommend with determining the ubiquitous language (UL) by interviewing the product owner(s). Establishing communication in a way that will have you and the product owners speaking the same language not only aides in communication, but being able to discuss the project in common terms tends to help the domain model define itself.
So, my answer is basically to discuss, listen, and learn. Software serves a need. Understanding the model from the viewpoint of the experts will lay the solid groundwork for the application.
I'd start by a drawing a class diagram with all the relationships and implement only the classes that are necessary according to the requirements of your application.
You can use an anemic approach (attributes plus getters and setters) to keep things simple and avoid the step of writing business logic in the same step. With an anemic model, the logic would go into a corresponding Service class. That way you can consider Use Cases later on.
I know some people don't appreciate this way of doing things but it does help with maintenance and avoids some dependency issues.
Answer to devoured elysium's question below:
In terms of analysis, starting with Use cases (What) and then proceeding to the class diagram (How) sounds like a good rule of thumb. Personally, I'd do the Sequence diagram (When and Who?) afterwards, as you'd need to know between which processes/objects messages need to be sent.
Beyond that my take on things is that UML is simply a way to model a system/project and not a methodology by itself (unlike Merise, RAD, RUP, Scrum, etc.). There is nothing stopping someone starting off with any diagram as long as they have the sufficient information to complete it. In fact, they should be done simultaneously since each of the diagrams is a different perspective of the same system/project.
So, all in all it depends on how you go about the analysis. During my studies I was taught the rigid waterfall approach, where you do a complete analysis from start to finish before producing some code. However, things can be different in practice, as the imperative might be to produce a working application in the least time possible.
For example, I was introduced to the Scrum methodology recently for an exercise involving the creation of a web site where people can post their fictions. As there was a time constraint and a clear vision of what should be achieved, we started right away with a bare bones class diagram to represent the domain model. The Use cases were then deduced from a series of mock screens we'd produced.
From memory, the classes were Story, Chapter, User and Category. This last class was phased out in favour of a more flexible Tag class. As you'd imagine, the complete class diagram of the existing project would be much more complex due to applying domain driven design and the specificities of the Java programming language.
This approach could be viewed as sloppy. However, a web site like this could easily be made in a couple of weeks using an iterative process and still be well designed. The advantage an iterative process has over the waterfall approach is that you can continually adjust requirements as you go. Frequent requirements changing is a reality, as people will often change their minds and the possibility of producing a working application after each iteration allows one to stay on course so to speak.
Of course, when you're presenting a project to a client, a complete analysis with UML diagrams and some mock screens would be preferable so they have an idea of what you're offering. This is where the UML comes in. Once you've explained some of the visual conventions, an individual should be able to understand the diagrams.
To finish off, if you're in the situation where you're trying to determine what a client wants, it's probably a good idea to gradually build up a questionnaire you can bring with you. Interviewing a person is the only way you can determine what concepts/features are really needed for an application, and you should expect to go back in order to clarify certain aspects. Another tip would be to do some quick research on the web when you're confronted with a subject matter you're unfamiliar with.
In your example, this would be to go through the basics of anatomy. Among other things, this will help you decide what the model should contain and what granularity it should have (What group of organs should be considered? How precise does it need to be? Do only the organs need to modeled or should they be decomposed into their constituents like tissues, cells, chemical composition, etc. ?).
I think the place to start would be whatever feels logical and comfortable. It's probably best to start with the use cases, as they give you clear direction and goals, and help you avoid YAGNI situations. Given that you should be trying to develop a strong domain model, it shouldn't really matter, as the whole picture of the domain is important.
I would like to share my experience for such type of situations. I usually start with writing tests and code. And try to cover one end to end use case. This gives me fair enough idea about problem and at the end I also have something working with me which I can show case to my client. Most of the time subsequent stories build on top of previous one, but it also happens to me that subsequent stories require changes in the previous model I came up with. But this does not impact me as I already have good test coverage. In this way I came up with the model which fits for the current problem, not the model which maps the real world.
You start with Business Requirements which can be formalized or not. If formalized you would use Use Case Diagrams.
For example here are use case diagrams for an e-commerce app:
http://askuml.com/blog/e-commerce/
http://askuml.com/files/2010/07/e-commerce-use-case.jpg
http://askuml.com/files/2010/07/e-commerce-use-case2b.jpg
From these use cases, you can naturally deduce the business entities: product, category of product, shopping cart, ... that is start to prepare class diagrams.
This is best practice in many methodologies but this is also just common sense and natural.
Short answer
Pick a use case, draw some collaboration diagram (and a class diagram) to realize the domain objects involved. Concentrate only on those objects participated in order to accomplish use case goal. Write TDD test case to set the expectation and gradually model your domain classes to meet the expectations. TDD is very helpful to understand the expected behaviors and it helps to get the cleaner domain model. You will see your domain evolve gradually along with the TDD expectations.
Long answer
My personal experience with DDD was not easy. That was because we didn't have necessary foundations in the first place. Our team had many weak points in different areas; requirements were not captured properly and we only had a customer representative who was not really helpful (not involved). We didn't have a proper release plan and developers had a lack of Object Oriented concepts, best principles and so on. The major problem we had was spending so much time on trying to understand the domain logic. We sketched many class diagrams and we never got the domain model right, so we stopped doing that and found out what went wrong. The problem was that we tried too hard to understand the domain logic and instead of communicating we made assumptions on the requirements. We decided to change our approach, we applied TDD, we started writing the expected behavior and coded the domain model to meet the TDD's expectations. Sometimes we got stuck writing TDD test cases because we didn't understand the domain. We straight away talked to the customer representative and tried to get more input. We changed our release strategy; applied agile methodology and release frequently so that we got real feedback from the end user. However, needed to ensure the end user expectation was set at the right level. We refactored based on the feedback, and in that way the domain model evolved gradually. Subsequently, we applied design patterns to improve reusability and maintainability. My point here is that DDD alone cannot survive, we have to build the ecosystem that embraces the domain, developers must have strong OOP concepts and must appreciate TDD and unit test. I would say DDD sits on top of all the OOP techniques and practices.
I tend to do a lot of projects on short deadlines and with lots of code that will never be used again, so there's always pressure/temptation to cut corners. One rule I always stick to is encapsulation/loose coupling, so I have lots of small classes rather than one giant God class. But what else should I never compromise on?
Update - thanks for the great response. Lots of people have suggested unit testing, but I don't think that's really appropriate to the kind of UI coding I do. Usability / User acceptance testing seems much important. To reiterate, I'm talking about the BARE MINIMUM of coding standards for impossible deadline projects.
Not OOP, but a practice that helps in both the short and long run is DRY, Don't Repeat Yourself. Don't use copy/paste inheritance.
Not a OOP practice, but common sense ;-).
If you are in a hurry, and have to write a hack. Always add a piece of comment with the reasons. So you can trace it back and make a good solution later.
If you never had the time to come back, you always have the comment so you know, why the solution was chosen at the moment.
Use Source control.
No matter how long it takes to set up (seconds..), it will always make your life easier! (still it's not OOP related).
Naming. Under pressure you'll write horrible code that you won't have time to document or even comment. Naming variables, methods and classes as explicitly as possible takes almost no additional time and will make the mess readable when you must fix it. From an OOP point of view, using nouns for classes and verbs for methods naturally helps encapsulation and modularity.
Unit tests - helps you sleep at night :-)
This is rather obvious (I hope), but at the very least I always make sure my public interface is as correct as possible. The internals of a class can always be refactored later on.
no public class with mutable public variables (struct-like).
Before you know it, you refer to this public variable all over your code, and the day you decide this field is a computed one and must have some logic in it... the refactoring gets messy.
If that day is before your release date, it gets messier.
Think about the people (may even be your future self) who have to read and understand the code at some point.
Application of the single responsibility principal. Effectively applying this principal generates a lot of positive externalities.
Like everyone else, not as much OOP practices, as much as practices for coding that apply to OOP.
Unit test, unit test, unit test. Defined unit tests have a habit of keeping people on task and not "wandering" aimlessly between objects.
Define and document all hierarchical information (namespaces, packages, folder structures, etc.) prior to writing production code. This helps to flesh out object relations and expose flaws in assumptions related to relationships of objects.
Define and document all applicable interfaces prior to writing production code. If done by a lead or an architect, this practice can additionally help keep more junior-level developers on task.
There are probably countless other "shoulds", but if I had to pick my top three, that would be the list.
Edit in response to comment:
This is precisely why you need to do these things up front. All of these sorts of practices make continued maintenance easier. As you assume more risk in the kickoff of a project, the more likely it is that you will spend more and more time maintaining the code. Granted, there is a larger upfront cost, but building on a solid foundation pays for itself. Is your obstacle lack of time (i.e. having to maintain other applications) or a decision from higher up? I have had to fight both of those fronts to be able to adopt these kinds of practices, and it isn't a pleasant situation to be in.
Of course everything should be Unit tested, well designed, commented, checked into source control and free of bugs. But life is not like that.
My personal ranking is this:
Use source control and actually write commit comments. This way you have a tiny bit of documentation should you ever wonder "what the heck did I think when I wrote this?"
Write clean code or document. Clean well-written code should need little documentation, as it's meaning can be grasped from reading it. Hacks are a lot different. Write why you did it, what you do and what you'd like to do if you had the time/knowledge/motivation/... to do it right
Unit Test. Yes it's down on number three. Not because it's unimportant but because it's useless if you don't have the other two at least halfway complete. Writing Unit tests is another level of documentation what you code should be doing (among others).
Refactor before you add something. This might sound like a typical "but we don't have time for it" point. But as with many of those points it usually saves more time than it costs. At least if you have at least some experience with it.
I'm aware that much of this has already been mentioned, but since it's a rather subjective matter, I wanted to add my ranking.
[insert boilerplate not-OOP specific caveat here]
Separation of concerns, unit tests, and that feeling that if something is too complex it's probably not conceptualised quite right yet.
UML sketching: this has clarified and saved any amount of wasted effort so many times. Pictures are great aren't they? :)
Really thinking about is-a's and has-a's. Getting this right first time is so important.
No matter how fast a company wants it, I pretty much always try to write code to the best of my ability.
I don't find it takes any longer and usually saves a lot of time, even in the short-term.
I've can't remember ever writing code and never looking at it again, I always make a few passes over it to test and debug it, and even in those few passes practices like refactoring to keep my code DRY, documentation (to some degree), separation of concerns and cohesion all seem to save time.
This includes crating many more small classes than most people (One concern per class, please) and often extracting initialization data into external files (or arrays) and writing little parsers for that data... Sometimes even writing little GUIs instead of editing data by hand.
Coding itself is pretty quick and easy, debugging crap someone wrote when they were "Under pressure" is what takes all the time!
At almost a year into my current project I finally set up an automated build that pushes any new commits to the test server, and man, I wish I had done that on day one. The biggest mistake I made early-on was going dark. With every feature, enhancement, bug-fix etc, I had a bad case of the "just one mores" before I would let anyone see the product, and it literally spiraled into a six month cycle. If every reasonable change had been automatically pushed out it would have been harder for me to hide, and I would have been more on-track with regard to the stakeholders' involvement.
Go back to code you wrote a few days/weeks ago and spend 20 minutes reviewing your own code. With the passage of time, you will be able to determine whether your "off-the-cuff" code is organized well enough for future maintenance efforts. While you're in there, look for refactoring and renaming opportunities.
I sometimes find that the name I chose for a function at the outset doesn't perfectly fit the function in its final form. With refactoring tools, you can easily change the name early before it goes into widespread use.
Just like everybody else has suggested these recommendations aren't specific to OOP:
Ensure that you comment your code and use sensibly named variables. If you ever have to look back upon the quick and dirty code you've written, you should be able to understand it easily. A general rule that I follow is; if you deleted all of the code and only had the comments left, you should still be able to understand the program flow.
Hacks usually tend to be convoluted and un-intuitive, so some good commenting is essential.
I'd also recommend that if you usually have to work to tight deadlines, get yourself a code library built up based upon your most common tasks. This will allow you to "join the dots" rather than reinvent the wheel each time you have a project.
Regards,
Docta
An actual OOP practice I always make time for is the Single Responsibility Principle, because it becomes so much harder to properly refactor the code later on when the project is "live".
By sticking to this principle I find that the code I write is easily re-used, replaced or rewritten if it fails to match the functional or non-functional requirements. When you end up with classes that have multiple responsibilities, some of them may fulfill the requirements, some may not, and the whole may be entirely unclear.
These kinds of classes are stressful to maintain because you are never sure what your "fix" will break.
For this special case (short deadlines and with lots of code that will never be used again) I suggest you to pay attention to embedding some script engine into your OOP code.
Learn to "refactor as-you-go". Mainly from an "extract method" standpoint. When you start to write a block of sequential code, take a few seconds to decide if this block could stand-alone as a reusable method and, if so, make that method immediately. I recommend it even for throw-away projects (especially if you can go back later and compile such methods into your personal toolbox API). It doesn't take long before you do it almost without thinking.
Hopefully you do this already and I'm preaching to the choir.
So no doubt that building a domain model is something that I think happens best when you approach it as as team. Even going so far as to involve someone who is not technical and a member of the 'business' in the modeling sessions. So much can get done quickly when you put the right people in a room and hammer out things on a whiteboard. But what about the times that you don't have that luxury? What about when you have to build a complex domain model alone? I have been doing this for the past month or so and have done the following:
Start off by Noun Idendtification, then use Class-Role-Collaborations to analyze relationships
Look for analysis patterns that can be used to refine the model, Party, etc..
As soon as I have a handle on the basics, I'll bust out an IDE and start writing XUnit tests to show that the model let's me do the things that I want
While these techniques have worked well, I'm not sure they are as efficient as a truely collaborative effort. I think it is easy to get carried away with a concept only to realize later that it violates x or y requirement. What techniques have you used when working in isolation to ensure that your object/domain model is on target?
Everyone does it differently, I think, but...
I almost always start with a Class diagram (usually UML-like and on paper), paying special attention to relationships between classes and their arity. Validation at this stage is mostly trying to understand if the high-level semantics of the entities make sense together.
Then start sketching in the key functions, especially those involved in collaborations. Make sure objects in a collaboration can reach each other through the relationships. At this stage I'll be using a drawing tool (StarUML).
Then come the gedanken experiments. I mentally walk through the trickiest use cases I can think of and see if I can envision a way to address them with the given design. This isn't psuedocode, just stepping through each of the major tasks/functions and following the lines of the diagram to make sure I'm not missing callbacks, circular dependencies, etc.
I think one key is to not get too married to any particular aspect of the design until you've satisfied yourself that it will probably work reasonably well. In my mind, if you can't step through a design mentally to evaluate/validate it you either lack some understanding of the problem, or the design on paper isn't complete enough...
Then, time permitting, set that one aside and see if you can come up with something really different...
If you're building it all on your own, just make sure it's adaptable, because there's no way you'll think of everything on the first shot.
Get some big paper. Draw everything out, and be messy. Don't worry about making it perfect. Put everything down that you think of, cross out stuff as it proves to not be useful. The paper will look like your mind threw up pieces of an object model all over the place. As you think of things that have already been written down, make those things stand out. At the end of this process, you'll have a mess, but for sure you'll have a lot of good ideas. At this point, I would recommend showing this to people, but since you said that's out of the question, we'll move on.
Now sit down in front of a computer with a UML tool and map out something that resembles the highlights of your brain dump. Think of the major pieces of the object model and then think of the more minor things that enable those pieces to work together. Once you have settled on something, turn that UML into code and go about writing some tests to see if it works. Rinse and repeat.
Everyone I work with is obsessed with the data-centric approach to enterprise development and hates the idea of using custom collections/objects. What is the best way to convince them otherwise?
Do it by example and tread lightly. Anything stronger will just alienate you from the rest of the team.
Remember to consider the possibility that they're onto something you've missed. Being part of a team means taking turns learning & teaching.
No single person has all the answers.
If you are working on legacy code (e.g., apps ported from .NET 1.x to 2.0 or 3.5) then it would be a bad idea to depart from datasets. Why change something that already works?
If you are, however, creating a new apps, there a few things that you can cite:
Appeal to experiencing pain in maintaining apps that stick with DataSets
Cite performance benefits for your new approach
Bait them with a good middle-ground. Move to .NET 3.5, and promote LINQ to SQL, for instance: while still sticking to data-driven architecture, is a huge, huge departure to string-indexed data sets, and enforces... voila! Custom collections -- in a manner that is hidden from them.
What is important is that whatever approach you use you remain consistent, and you are completely honest with the pros and cons of your approaches.
If all else fails (e.g., you have a development team that utterly refuses to budge from old practices and is skeptical of learning new things), this is a very, very clear sign that you've outgrown your team it's time to leave your company!
Remember to consider the possibility that they're onto something you've missed. Being part of a team means taking turns learning & teaching.
Seconded. The whole idea that "enterprise development" is somehow distinct from (and usually the implication is 'more important than') normal development really irks me.
If there really is a benefit for using some technology, then you'll need to come up with a considered list of all the pros and cons that would occur if you switched.
Present this list to your co workers along with explanations and examples for each one.
You have to be realistic when creating this list. You can't just say "Saves us lots of time!!! WIN!!" without addressing the fact that sometimes it is going to take MORE time, will require X months to come up to speed on the new tech, etc. You have to show concrete examples where it will save time, and exactly how.
Likewise you can't just skirt over the cons as if they don't matter, your co-workers will call you on it.
If you don't do these things, or come across as just pushing what you personally like, nobody is going to take you seriously, and you'll just get a reputation for being the guy who's full of enthusiasm and energy but has no idea about anything.
BTW. Look out for this particular con. It will trump everything, unless you have a lot of strong cases for all your other stuff:
Requires 12+ months work porting our existing code. You lose.
Of course, "it depends" on the situation. Sometimes DataSets or DataTables are more suited, like if it really is pretty light business logic, flat hierarchy of entities/records, or featuring some versioning capabilities.
Custom object collections shine when you want to implement a deep hierarchy/graph of objects that cannot be efficiently represented in flat 2D tables. What you can demonstrate is a large graph of objects and getting certain events to propagate down the correct branches without invoking inappropriate objects in other branches. That way it is not necessary to loop or Select through each and every DataTable just to get the child records.
For example, in a project I got involved in two and half years ago, there was a UI module that is supposed to display questions and answer controls in a single WinForms DataGrid (to be more specific, it was Infragistics' UltraGrid). Some more tricky requirements
The answer control for a question can be anything - text box, check box options, radio button options, drop-down lists, or even to pop up a custom dialog box that may pull more data from a web service.
Depending on what the user answered, it can trigger more sub-questions to appear directly under the parent question. If a different answer is given later, it should expose another set of sub-questions (if any) related to that answer.
The original implementation was written entirely in DataSets, DataTables, and arrays. The amount of looping through the hundreds of rows for multiple tables was purely mind-bending. It did not help the programmer came from a C++ background attempting to ref everything (hello, objects living in the heap use reference variables, like pointers!). Nobody, not even the originally programmer, could explain why the code is doing what it does. I came into the scene more than six months after this, and it was stil flooded with bugs. No wonder the 2nd-generation developer I took over from decided to quit.
Two months of tying to fix the chaotic mess, I took it upon myself to redesign the entire module into an object-oriented graph to solve this problem. yeap, complete with abstract classes (to render different answer control on a grid cell depending on question type), delegates and eventing. The end result was a 2D dataGrid binded to a deep hierarchy of questions, naturally sorted according to the parent-child arrangement. When a parent question's answer changed, it would raise an event to the children questions and they would automatically show/hide their rows in the grid according to the parent's answer. Only question objects down that path were affected. The UI responsiveness of this solution compared to the old method was by orders of magnitude.
Ironically, I wanted to post a question that was the exact opposite of this. Most of the programmers I've worked with have gone with the custom data objects/collections approach. It breaks my heart to watch someone with their SQL Server table definition open on one monitor, slowly typing up a matching row-wrapper class in Visual Studio in another monitor (complete with private properties and getters-setters for each column). It's especially painful if they're also prone to creating 60-column tables. I know there are ORM systems that can build these classes automagically, but I've seen the manual approach used much more frequently.
Engineering choices always involve trade-offs between the pros and cons of the available options. The DataSet-centric approach has its advantages (db-table-like in-memory representation of actual db data, classes written by people who know what they're doing, familiar to large pool of developers etc.), as do custom data objects (compile-type checking, users don't need to learn SQL etc.). If everyone else at your company is going the DataSet route, it's at least technically possible that DataSets are the best choice for what they're doing.
Datasets/tables aren't so bad are they?
Best advise I can give is to use it as much as you can in your own code, and hopefully through peer reviews and bugfixes, the other developers will see how code becomes more readable. (make sure to push the point when these occurrences happen).
Ultimately if the code works, then the rest is semantics is my view.
I guess you can trying selling the idea of O/R mapping and mapper tools. The benefit of treating rows as objects is pretty powerful.
I think you should focus on the performance. If you can create an application that shows the performance difference when using DataSets vs Custom Entities. Also, try to show them Domain Driven Design principles and how it fits with entity frameworks.
Don't make it a religion or faith discussion. Those are hard to win (and is not what you want anyway)
Don't frame it the way you just did in your question. The issue is not getting anyone to agree that this way or that way is the general way they should work. You should talk about how each one needs to think in order to make the right choice at any given time. give an example for when to use dataSet, and when not to.
I had developers using dataTables to store data they fetched from the database and then have business logic code using that dataTable... And I showed them how I reduced the time to load a page from taking 7 seconds of 100% CPU (on the web server) to not being able to see the CPU line move at all.. by changing the memory object from dataTable to Hash table.
So take an example or case that you thing is better implemented differently, and win that battle. Don't fight the a high level war...
If Interoperability is/will be a concern down the line, DataSet is definitely not the right direction to go in. You CAN expose DataSets/DataTables over a service but whether you SHOULD or is debatable. If you are talking .NET->.NET you're probably Ok, otherwise you are going to have a very unhappy client developer from the other side of the fence consuming your service
You can't convince them otherwise. Pick a smaller challenge or move to a different organization. If your manager respects you see if you can do a project in the domain-driven style as a sort of technology trial.
If you can profile, just Do it and profile. Datasets are heavier then a simple Collection<T>
DataReaders are faster then using Adapters...
Changing behavior in an objects is much easier than massaging a dataset
Anyway: Just Do It, ask for forgiveness not permission.
Most programmers don't like to stray out of their comfort zones (note that the intersection of the 'most programmers' set and the 'Stack Overflow' set is the probably the empty set). "If it worked before (or even just worked) then keep on doing it". The project I'm currently on required a lot of argument to get the older programmers to use XML/schemas/data sets instead of just CSV files (the previous version of the software used CSV's). It's not perfect, the schemas aren't robust enough at validating the data. But it's a step in the right direction. The code I develop uses OO abstractions on the data sets rather than passing data set objects around. Generally, it's best to teach by example, one small step at a time.
There is already some very good advice here but you'll still have a job to convince your colleagues if all you have to back you up is a few supportive comments on stackoverflow.
And, if they are as sceptical as they sound, you are going to need more ammo.
First, get a copy of Martin Fowler's "Patterns of Enterprise Architecture" which contains a detailed analysis of a variety of data access techniques.
Read it.
Then force them all to read it.
Job done.
data-centric means less code-complexity.
custom objects means potentially hundreds of additional objects to organize, maintain, and generally live with. It's also going to be a bit faster.
I think it's really a code-complexity vs performance question, which can be answered by the needs of your app.
Start small. Is there a utility app you can use to illustrate your point?
For instance, at a place where I worked, the main application had a complicated build process, involving changing config files, installing a service, etc.
So I wrote an app to automate the build process. It had a rudimentary WinForms UI. But since we were moving towards WPF, I changed it to a WPF UI, while keeping the WinForms UI as well, thanks to Model-View-Presenter. For those who weren't familiar with Model-View-Presenter, it was an easily-comprehensible example they could refer to.
Similarly, find something small where you can show them what a non-DataSet app would look like without having to make a major development investment.