In computing, reactive programming is a programming paradigm oriented around data flows and the
propagation of change. This means that it should be possible to express static or dynamic
data flows with ease in the programming languages used, and that the underlying execution model
will automatically propagate changes through the data flow.
For example, in an imperative programming setting, would mean that is being assigned
the result of in the instant the expression is evaluated. Later, the values of and can
be changed with no effect on the value of .
In reactive programming, the value of would be automatically updated based on the new
values. A modern spreadsheet program is an example
of reactive programming. Spreadsheet cells can contain literal values, or formulas such
as "=B1+C1" that are evaluated based on other cells. Whenever the value of the other cells
change, the value of the formula is automatically updated.
Another example is a hardware description language such as Verilog. In this case reactive
programming allows us to model changes as they propagate through a circuit.
Reactive programming has foremost been proposed as a way to simplify the creation of interactive
user interfaces, animations in real time systems, but is essentially a general programming paradigm.
For example, in a Model-view-controller architecture, reactive programming can allow changes in
the underlying model to automatically be reflected in the view, and vice versa.
Concepts Degrees of explicitness
Reactive programming languages can range from very explicit ones where data flows are set
up by using arrows, to implicit where the data flows are derived from language constructs
that look similar to those of imperative or functional programming. For example, in implicitly
lifted functional reactive programming a function call might implicitly cause a node in a data
flow graph to be constructed. Reactive programming libraries for dynamic languages can construct
a dependency graph from runtime analysis of the values read during a function's execution,
allowing data flow specifications to be both implicit and dynamic.
Sometimes the term reactive programming refers to the architectural level of software engineering,
where individual nodes in the data flow graph are ordinary programs that communicate with
each other. Static or Dynamic
Reactive programming can be purely static where the data flows are set up statically,
or be dynamic where the data flows can change during the execution of a program.
The use of data switches in the data flow graph could to some extent make a static data
flow graph appear as dynamic, and blur the distinction slightly. True dynamic reactive
programming however could use imperative programming to reconstruct the data flow graph.
Higher-order reactive programming Reactive programming could be said to be of
higher order if it supports the idea that data flows could be used to construct other
data flows. That is, the resulting value out of a data flow is another data flow graph
that is executed using the same evaluation model as the first.
Data flow differentiation Ideally all data changes are propagated instantly,
but this cannot be assured in practice. Instead it might be necessary to give different parts
of the data flow graph different evaluation priorities. This can be called differentiated
reactive programming. For example, in a word processor the marking
of spelling errors need not be totally in sync with the inserting of characters. Here
differentiated reactive programming could potentially be used to give the spell checker
lower priority, allowing it to be delayed while keeping other data-flows instantaneous.
However, such differentiation introduces additional design complexity. For example, deciding how
to define the different data flow areas, and how to handle event passing between different
data flow areas. Evaluation models of reactive programming
Evaluation of reactive programs is not necessarily based on how stack based programming languages
are evaluated. Instead, when some data is changed, the change is propagated to all data
that is derived partially or completely from the data that was changed. This change propagation
could be achieved in a number of ways, where perhaps the most natural way is an invalidate/lazy-revalidate
scheme. It could be problematic to just naively propagate
a change using a stack, because of potential exponential update complexity if the data
structure has a certain shape. One such shape can be described as "repeated diamonds shape",
and has the following structure: An→Bn→An+1, An→Cn→An+1, where n=1,2... This problem
could be overcome by propagating invalidation only when some data is not already invalidated,
and later re-validate the data when needed using lazy evaluation.
One inherent problem for reactive programming is that most computations that would be evaluated
and forgotten in a normal programming language, needs to be represented in the memory as data-structures.
This could potentially make RP highly memory consuming. However, research on what is called
lowering could potentially overcome this problem. On the other side, reactive programming is
a form of what could be described as "explicit parallelism", and could therefore be beneficial
for utilizing the power of parallel hardware. Similarities with observer pattern
Reactive programming has principal similarities with the observer pattern commonly used in
object-oriented programming. However, integrating the data flow concepts into the programming
language would make it easier to express them, and could therefore increase the granularity
of the data flow graph. For example, the observer pattern commonly describes data-flows between
whole objects/classes, whereas object-oriented reactive programming could target the members
of objects/classes. The stack-based evaluation model of common
object orientation is also not entirely suitable for data-flow propagation, as occurrences
of the "repeated diamond shape" in the data structures could make the program face exponential
complexities. But because of its relatively limited use and low granularity, this is rarely
a problem for the observer pattern in practice. Approaches
Imperative It is possible to fuse reactive programming
with ordinary imperative programming. In such a paradigm, imperative programs operate upon
reactive data structures. Such a set-up is analogous to constraint imperative programming;
however, while constraint imperative programming manages bidirectional constraints, reactive
imperative programming manages one-way dataflow constraints.
Object-oriented Object-oriented reactive programming is a
combination of object oriented programming and reactive programming. Perhaps the most
natural way to make such a combination is as follows: Instead of methods and fields,
objects have reactions that automatically re-evaluate when the other reactions they
depend on have been modified. Below an illustration of the A=X+Y introductory example:
If an OORP programming language maintains its imperative methods, it would also fall
under the category of imperative reactive programming.
The OOPic microprocessor supports this style of programming via its virtual circuits.
Functional Functional reactive programming is a programming
paradigm for reactive programming on functional programming.
See also QML
Elm Reactive composition of web user interface. RxJS
References ^ Trellis, Model-view-controller and the observer
pattern, Tele community . ^ Burchett, Kimberley; Cooper, Gregory H;
Krishnamurthi, Shriram, "Lowering: a static optimization technique for transparent functional
reactivity", Proceedings of the 2007 ACM SIGPLAN symposium on Partial evaluation and semantics-based
program manipulation, pp. 71–80 . ^ Demetrescu, Camil; Finocchi, Irene; Ribichini,
Andrea, "Reactive Imperative Programming with Dataflow Constraints", Proceedings of the
2011 ACM international conference on Object oriented programming systems languages and
applications, pp. 407–26 . ^ example of A=X+Y, JS fiddle .
External links A survey on reactive programming A paper by
E. Bainomugisha, A. Lombide Carreton, T. Van Cutsem, S. Mostinckx, and W. De Meuter that
surveys and provides a taxonomy of existing reactive programming approaches.
MIMOSA Project of INRIA - ENSMP, a general site about reactive programming.
Experimenting with Cells Demonstration of a simple reactive programming application
in Lisp, using the Cells library REScala Reactive programming for OO applications.
Reactive Programming in .NET Microsoft's Reactive Extensions homepage
Deprecating the Observer Pattern A paper by Ingo Maier, Tiark Rompf and Martin Odersky
outlining a reactive programming framework for the Scala programming language.
The Reactive Manifesto a site describing the importance of Reactive Applications