Model-View-Presenter
In MVP, the Presenter contains the UI business logic for the View. All invocations from the View delegate directly to the Presenter. The Presenter is also decoupled directly from the View and talks to it through an interface. This is to allow mocking of the View in a unit test. One common attribute of MVP is that there has to be a lot of two-way dispatching. For example, when someone clicks the "Save" button, the event handler delegates to the Presenter's "OnSave" method. Once the save is completed, the Presenter will then call back the View through its interface so that the View can display that the save has completed.
MVP tends to be a very natural pattern for achieving separated presentation in WebForms. The reason is that the View is always created first by the ASP.NET runtime. You can find out more about both variants.
Two primary variations
Passive View: The View is as dumb as possible and contains almost zero logic. A Presenter is a middle man that talks to the View and the Model. The View and Model are completely shielded from one another. The Model may raise events, but the Presenter subscribes to them for updating the View. In Passive View there is no direct data binding, instead, the View exposes setter properties that the Presenter uses to set the data. All state is managed in the Presenter and not the View.
- Pro: maximum testability surface; clean separation of the View and Model
- Con: more work (for example all the setter properties) as you are doing all the data binding yourself.
Supervising Controller: The Presenter handles user gestures. The View binds to the Model directly through data binding. In this case, it's the Presenter's job to pass off the Model to the View so that it can bind to it. The Presenter will also contain logic for gestures like pressing a button, navigation, etc.
- Pro: by leveraging data binding the amount of code is reduced.
- Con: there's a less testable surface (because of data binding), and there's less encapsulation in the View since it talks directly to the Model.
Model-View-Controller
In the MVC, the Controller is responsible for determining which View to display in response to any action including when the application loads. This differs from MVP where actions route through the View to the Presenter. In MVC, every action in the View correlates with a call to a Controller along with an action. In the web, each action involves a call to a URL on the other side of which there is a Controller who responds. Once that Controller has completed its processing, it will return the correct View. The sequence continues in that manner throughout the life of the application:
Action in the View
-> Call to Controller
-> Controller Logic
-> Controller returns the View.
One other big difference about MVC is that the View does not directly bind to the Model. The view simply renders and is completely stateless. In implementations of MVC, the View usually will not have any logic in the code behind. This is contrary to MVP where it is absolutely necessary because, if the View does not delegate to the Presenter, it will never get called.
Presentation Model
One other pattern to look at is the Presentation Model pattern. In this pattern, there is no Presenter. Instead, the View binds directly to a Presentation Model. The Presentation Model is a Model crafted specifically for the View. This means this Model can expose properties that one would never put on a domain model as it would be a violation of separation-of-concerns. In this case, the Presentation Model binds to the domain model and may subscribe to events coming from that Model. The View then subscribes to events coming from the Presentation Model and updates itself accordingly. The Presentation Model can expose commands which the view uses for invoking actions. The advantage of this approach is that you can essentially remove the code-behind altogether as the PM completely encapsulates all of the behavior for the view. This pattern is a very strong candidate for use in WPF applications and is also called Model-View-ViewModel.
There is a MSDN article about the Presentation Model and a section in the Composite Application Guidance for WPF (former Prism) about Separated Presentation Patterns
The name reflection is used to describe code which is able to inspect other code in the same system (or itself).
For example, say you have an object of an unknown type in Java, and you would like to call a 'doSomething' method on it if one exists. Java's static typing system isn't really designed to support this unless the object conforms to a known interface, but using reflection, your code can look at the object and find out if it has a method called 'doSomething' and then call it if you want to.
So, to give you a code example of this in Java (imagine the object in question is foo) :
Method method = foo.getClass().getMethod("doSomething", null);
method.invoke(foo, null);
One very common use case in Java is the usage with annotations. JUnit 4, for example, will use reflection to look through your classes for methods tagged with the @Test annotation, and will then call them when running the unit test.
There are some good reflection examples to get you started at http://docs.oracle.com/javase/tutorial/reflect/index.html
And finally, yes, the concepts are pretty much similar in other statically typed languages which support reflection (like C#). In dynamically typed languages, the use case described above is less necessary (since the compiler will allow any method to be called on any object, failing at runtime if it does not exist), but the second case of looking for methods which are marked or work in a certain way is still common.
Update from a comment:
The ability to inspect the code in the system and see object types is
not reflection, but rather Type Introspection. Reflection is then the
ability to make modifications at runtime by making use of
introspection. The distinction is necessary here as some languages
support introspection, but do not support reflection. One such example
is C++
Best Answer
If you want to get a feel for FRP, you could start with the old Fran tutorial from 1998, which has animated illustrations. For papers, start with Functional Reactive Animation and then follow up on links on the publications link on my home page and the FRP link on the Haskell wiki.
Personally, I like to think about what FRP means before addressing how it might be implemented. (Code without a specification is an answer without a question and thus "not even wrong".) So I don't describe FRP in representation/implementation terms as Thomas K does in another answer (graphs, nodes, edges, firing, execution, etc). There are many possible implementation styles, but no implementation says what FRP is.
I do resonate with Laurence G's simple description that FRP is about "datatypes that represent a value 'over time' ". Conventional imperative programming captures these dynamic values only indirectly, through state and mutations. The complete history (past, present, future) has no first class representation. Moreover, only discretely evolving values can be (indirectly) captured, since the imperative paradigm is temporally discrete. In contrast, FRP captures these evolving values directly and has no difficulty with continuously evolving values.
FRP is also unusual in that it is concurrent without running afoul of the theoretical & pragmatic rats' nest that plagues imperative concurrency. Semantically, FRP's concurrency is fine-grained, determinate, and continuous. (I'm talking about meaning, not implementation. An implementation may or may not involve concurrency or parallelism.) Semantic determinacy is very important for reasoning, both rigorous and informal. While concurrency adds enormous complexity to imperative programming (due to nondeterministic interleaving), it is effortless in FRP.
So, what is FRP? You could have invented it yourself. Start with these ideas:
Dynamic/evolving values (i.e., values "over time") are first class values in themselves. You can define them and combine them, pass them into & out of functions. I called these things "behaviors".
Behaviors are built up out of a few primitives, like constant (static) behaviors and time (like a clock), and then with sequential and parallel combination. n behaviors are combined by applying an n-ary function (on static values), "point-wise", i.e., continuously over time.
To account for discrete phenomena, have another type (family) of "events", each of which has a stream (finite or infinite) of occurrences. Each occurrence has an associated time and value.
To come up with the compositional vocabulary out of which all behaviors and events can be built, play with some examples. Keep deconstructing into pieces that are more general/simple.
So that you know you're on solid ground, give the whole model a compositional foundation, using the technique of denotational semantics, which just means that (a) each type has a corresponding simple & precise mathematical type of "meanings", and (b) each primitive and operator has a simple & precise meaning as a function of the meanings of the constituents. Never, ever mix implementation considerations into your exploration process. If this description is gibberish to you, consult (a) Denotational design with type class morphisms, (b) Push-pull functional reactive programming (ignoring the implementation bits), and (c) the Denotational Semantics Haskell wikibooks page. Beware that denotational semantics has two parts, from its two founders Christopher Strachey and Dana Scott: the easier & more useful Strachey part and the harder and less useful (for software design) Scott part.
If you stick with these principles, I expect you'll get something more-or-less in the spirit of FRP.
Where did I get these principles? In software design, I always ask the same question: "what does it mean?". Denotational semantics gave me a precise framework for this question, and one that fits my aesthetics (unlike operational or axiomatic semantics, both of which leave me unsatisfied). So I asked myself what is behavior? I soon realized that the temporally discrete nature of imperative computation is an accommodation to a particular style of machine, rather than a natural description of behavior itself. The simplest precise description of behavior I can think of is simply "function of (continuous) time", so that's my model. Delightfully, this model handles continuous, deterministic concurrency with ease and grace.
It's been quite a challenge to implement this model correctly and efficiently, but that's another story.