Context-oriented Programming
Robert Hirschfeld,
Hasso-Plattner-Institut, Universität Potsdam, Germany
Pascal Costanza,
Programming Technology Lab, Vrije Universiteit Brussel, Belgium
Oscar Nierstrasz,
Software Composition Group, Universität Bern, Switzerland
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Abstract
Context-dependent behavior is becoming increasingly important for a wide range of
application domains, from pervasive computing to common business applications. Unfortunately,
mainstream programming languages do not provide mechanisms that enable
software entities to adapt their behavior dynamically to the current execution
context. This leads developers to adopt convoluted designs to achieve the necessary
runtime flexibility. We propose a new programming technique called Context-oriented
Programming (COP) which addresses this problem. COP treats context explicitly, and
provides mechanisms to dynamically adapt behavior in reaction to changes in context,
even after system deployment at runtime. In this paper we lay the foundations of COP,
show how dynamic layer activation enables multi-dimensional dispatch, illustrate the
application of COP by examples in several language extensions, and demonstrate that
COP is largely independent of other commitments to programming style.
1 INTRODUCTION
Contextual information is playing an increasingly important role for applications
and services ranging from those that are location-based to those that are situationdependent
or even deeply personalized. While context-awareness is already an integral
part of regular business applications, it is becoming even more critical for
mobile and ubiquitous computing, where devices must adapt their behavior to the
services available in their current environment.
Despite the fact that context is clearly a central notion to an emerging class
of applications, there is little explicit support for context awareness in mainstream
programming languages and runtime environments. This makes the development of
these applications more complex than necessary. In this paper we argue the need for
a new programming approach, called Context-oriented Programming (COP), which
treats context explicitly and makes it accessible and manipulable by software.
One difficulty in proposing a concrete COP language is that context covers a
wide range of concepts ranging from domain-specific to technology-dependent attributes,
and including properties that may be spatial or temporal, or even based
in hardware or software. We see personalization, sharing, location-awareness, ubiquitous computing, software evolution, runtime adaptation, and xecution context
dependencies as a part of COP’s application domain.
At present, the lack of programming mechanisms to support the development
of context-aware applications forces the design of these applications to be more
complex and fragile than need be the case.
This paper presents Context-oriented Programming (COP) as a new programming
technique to enable context-dependent computation. We claim that Contextoriented
Programming brings a similar degree of dynamicity to the notion of behavioral
variations that object-oriented programming brought to ad-hoc polymorphism.
In support of this claim, we argue that the dynamic representation of layers and their
scoped activation and deactivation in arbitrary places of the code are the essential
ingredients for COP. Notably, in this paper we discuss:
- The motivation of Context-oriented Programming (COP) as a programming
technique that directly supports context-dependent behavioral variations.
- Layers as named first-class entities that can be referred to explicitly at runtime,
and whose composition can be dynamically controlled on-demand.
- An illustration of the utility of COP by several examples implemented in different COP extensions to Java, Squeak/Smalltalk and Common Lisp.
Specifically, we show as the contributions of this paper that:
- COP is independent from how source code is organized into textual modules.
- It can be beneficial to activate/deactivate layers from anywhere in the code.
- The notion of layered slots in ContextL allows a higher-order reflective programming
style to integrate crosscutting concerns.
2 PROBLEMS
A context-dependent application varies its behavior according to conditions arising
during execution. In order to pin down the term context, we offer the following
abstract picture of context-dependence (see Figures 1a, b, and c).
An actor (as in UML) is an entity that interacts with the system, calling functions,
sending messages, or employing other means of interaction in order to request
the desired system behavior. A system is a computational entity that provides some
desired behavior whenever requested. A system may be large or small, finely-grained
or coarsely-grained. The constituents of a system may, for example, be procedures,
methods, objects, components or subsystems. An environment represents anything
external to the relationship and interaction between actor and system.
Figure 1: Actor-, environment, and system-dependent behavior variations.
The actors, the system, and the environment each contribute to the context that
may influence the behavior of the application. Actor-dependent, system-dependent,
and environment-dependent variations are described independently and separately,
but can occur in any combination. Note that actor, system, and environment represent
distinct roles that depend on a particular point of view at a specific point
in time and can in principle be filled by all involved entities interchangeably. A
piece of software may play the role of the system in one interaction, the actor in
another, and provide the environmental context for yet a third. Examples of actors
and systems are senders and receivers of messages in object systems, or clients and
servers of remote procedures in distributed environments. Actor-dependent Behavior Variations
An example of actor-dependent behavior variation is that of multiple visualizations
of the same system or system entity, such as the rendering of statistical data as in
different kinds of charts. Here, an actor determines which information provided by
or obtainable from the system will be shown and in what form, contributing to the
context-dependent behavior of the system.
A system needs to behave differently not only in response to different requests,
but often also in response to the same request by different actors (Figure 1a).
Environment-dependent Behavior Variations An environment-dependent behavior variation is essentially any conditional guarding
a subset of application behavior or execution. Examples are anything that is not
given implicitly by the flow of control in the execution of a piece of code but needs
to be checked explicitly, such as the object a variable is referring to, the time of
day, the battery status of the current device, or the temperature read out of sensory
equipment. Often, related code is scattered over several system parts to coordinate
activation or blocking of related environment-dependent behavior variations.
A system’s response to a stimulus initiated by an actor may need to be adjusted
to take into account properties of the computational environment. Here, the system’s
behavior can be affected by anything adjunct to the immediate interaction between
actor and system (Figure 1b).
System-dependent Behavior Variations
An example of system-dependent behavior variation is that of change notification,
the dissemination of information about what system parts have changed, and how.
The way change notifications can be observed should depend on the relationships
between the various system parts involved or affected. Often, multiple and redundant
notifications are generated for a single change, resulting in cascading updates
or other undesirable effects.
A system may need to vary its behavior depending on its own current state,
historical information, or dependencies to other system parts or subsystems. In such
case the context that influences behavioral variation is not determined by different
actors, but by the system itself (Figure 1c).
3 CONTEXT-ORIENTED PROGRAMMING
Context-oriented Programming enables the expression of behavioral variation dependent
on context. To analyze and distill what constructs are necessary to enable
expressing context-dependent behavioral variations, we have carried out a number
of application and language extension experiments. Among others, we have implemented
exception handling [2], multiple views on the same object which are selected
based on execution context [14], coordination of screen updates [16], discerning of
phone calls based on the context of both callers and callees [41], selecting billing
schemes based on dynamic context conditions [15], and traversals of expression
trees [26]. ContextL, our first language extension that explicitly supports our vision
of Context-oriented Programming, has already been integrated into Lisp on Lines, a
Web framework that is used in commercial applications [12], and is used for generating
different document formats (like html, pdf, etc.) from the same object structures.
In other settings, we have developed Piccola, a language with first-class namespaces
[1], a context-oriented extension of AspectS [25] for Smalltalk/Squeak, ContextS
for Smalltalk/Squeak, and context-oriented extensions of AmbientTalk [42].
Based on these implementations of both application scenarios and necessary language
extensions, we identify the following essential language properties to support
COP: (a) means to specify behavioral variations, (b) means to group variations
into layers, (c) dynamic activation and deactivation of layers based on context, and
(d) means to explicitly and dynamically control the scope of layers. Based on our fi ndings, approaches to COP should at least address the following properties: Based on these implementations of both application scenarios and necessary language
extensions, we identify the following essential language properties to support
COP: (a) a means to specify behavioral variations, (b) a means to group variations
into layers, (c) dynamic activation and deactivation of layers based on context, and
(d) means to explicitly and dynamically control the scope of layers. Based on our
findings, approaches to COP should at least address the following properties:
Behavioral variations. Variations typically consist of new or modified behavior,
but may also comprise removed behavior. They can be expressed as partial definitions
of modules in the underlying programming model such as procedures
or classes, with complete definitions representing just a special case. Variations
may also be expressed as edits, wrappers, or even general refactorings or
transformations.
Layers. Layers group related context-dependent behavioral variations. Layers are
first-class entities, so that they can be explicitly referred to in the underlying
programming model.
Activation. Layers aggregating context-dependent behavioral variations can be activated
and deactivated dynamically at runtime. Code can decide to enable or
disable layers of aggregate behavioral variations based on the current context.
Context. Any information which is computationally accessible may form part of
the context upon which behavioral variations depend.
Scoping. The scope within which layers are activated or deactivated can be controlled
explicitly. The same variations may be simultaneously active or not
within different scopes of the same running application.
Layers are composed in reaction to contextual information. Based on information
available in the current execution context, specific layers may be activated or
deactivated. COP languages and environment extensions provide the mechanisms
for expressing, activating and composing layers at runtime, but it is the application
domain that determines which contextual information is relevant. This last
part may be counter-intuitive, but based on our experience, it is indeed not necessary
to provide explicit support for context modeling, since existing object-oriented
abstraction mechanisms are sufficient to model context [17].
4 MULTI-DIMENSIONAL MESSAGE DISPATCH
Following Smith and Ungar [37], we present COP in the context of multi-dimensional
message dispatch. While this is not to suggest that COP implementations have to
be based on such concepts, we believe that this analogy will help the reader to
understand that COP is a continuation of other work, namely procedural, objectoriented,
and subjective programming.
One-dimensional dispatch. Procedural programming provides only one dimension
to associate a computational unit with a name [37]. Here, procedure calls or
names are directly mapped to procedure implementations. In Figure 2a calling m1 leaves no choice but the invocation of the only implementation of procedure m1.
Two-dimensional dispatch. Object-oriented programming adds another dimension
for name resolution to that of procedural programming [37]. In addition to
the method or procedure name, message dispatch takes the message receiver into
consideration when looking up a method. In Figure 2b we see two implementations
of method m1. The selection of the appropriate method not only depends on the the
message name m1, but also the receiver of the actual message, here Ry.
Three-dimensional dispatch. Subjective programming as introduced by Smith
and Ungar [37] extends object-oriented method dispatch by yet another dimension.
Figure 2: One-, two-, and three-dimensional method dispatch.
Figure 3: Four-dimensional method dispatch.
Here, methods are not only selected based on the name of a message and its receiver
but also on its sender. In Figure 2c sender SA sends message m1 to receiver Ry. Ry implements two methods m1: The first one is associated with any sender (m1:*), but
the second one only with sender SB (m1:SB). This is why, in our example, m1:* is
selected for execution.
Four-dimensional dispatch. Context-oriented Programming takes subjective programming
one step further by dispatching not only on the name of a message, its
sender and its receiver, but also on the context of the actual message send. Context,
as stated in Section 3, is anything that is computationally accessible, either directly
or derived. Based on context information, methods or their partial definitions are
selected for or excluded from message dispatch, leading to context-dependent behavioral
variations as described in the previous sections.
In Figure 3 there are two scenarios showing how context can affect method
dispatch in COP environments. In both scenarios a message m1 is sent to the same
receiver Ry, from different senders (SA and SB), and in different contexts (Cα and Cβ). In Figure 3a, our selection process results in method m1:*:Cβ. This is because
that particular partial method implementation matches with messages m1, sent to
receivers Ry , by any sender (* is matched by sender SA), in both contexts Cα or Cβ.
In Figure 3b, our selection process results also in method m1:*:Cβ, now because the
message and its sender and receiver correspond to the method’s properties as before,
and in addition to that context Cβ matches with m1’s Cβ property as well. Method m1:*:Cα will not match with our request due to incompatible context properties.
Please note that combinations of context-conditions can be considered in method
dispatch but are not discussed in this paper.
Figure 4: Layers providing different display behavior.
5 EXAMPLES
In this section, we come back to the problems described in Section 2 and use
them to both describe COP-based example solutions as well as language extensions.
We first discuss actor-dependent behavior variations using ContextJ for Java
to implement multiple views on objects. Then, we show how to conditionally activate
and deactivate behavioral variations based on explicitly checking properties
that are not directly associated with the current flow of control using ContextS
for Squeak/Smalltalk. Finally, we illustrate system-dependent behavior variations
based on an implementation of change notifications in ContextL for Lisp.
In addition to illustrating how COP can be used to address context changes
caused by actors, the environment, and the system itself, our examples also show
how behavorial variations can be expressed in different ways. While examples discussed
in our previous publications about COP [13, 15] are expressed in a style
close to aspect- and feature-oriented programming, we deviate here in several ways.
Specifically, we show that (a) placing the behavioral variations associated with layers
in the respective class definitions instead of textually modularizing layers is a valid
organization of the source code for COP, (b) there is no need to expose AOP-style
join points to enable the use of layer activation and deactivation, and (c) the notion
of context-dependent behavioral variations expressed as layers is compatible with a
higher-order reflective programming style to handle crosscutting concerns.
Actor-dependent Behavior Variations
The following example is expressed in ContextJ. We consider ContextJ to be very
helpful in illustrating COP language constructs to programmers more
uent in mainstream
programming languages than in Lisp or Smalltalk. A different variant of
ContextJ was already used as a means to ease the accessibility of a ContextL-based
example [16].1 The code in Figure 4 is a simplified version of an earlier example [14]. Here,
we focus on elements essential to this paper showing a ContextJ implementation of
actor-dependent behavior variations where the views a system presents to its clients
depend on the clients requesting such views.
In Figure 4, we define the classes Person and Employer with fields name, address and employer, together with the necessary constructors and a default toString method. We also define the two layers Address and Employment that define behavioral
variations on toString. In the Address layer, address information is returned
for instances of Person and Employer in addition to the default behavior of toString. The call to the special method proceed ensures that the original definition of toString is called. In this sense, proceed is similar to super in Java for
performing supercalls, or proceed in AspectJ for calling original method definitions
from around advice. The toString method in layer Employment returns additional
information about the employer of a person in the Person class.
None of the user-defined layers Address and Employment are activated by default.
Instead, a client program must explicitly choose to activate them when desired.
ContextJ provides with and without for activation and deactivation of layers with
dynamic scope.
Here, the purpose is to present different views on the same program where each
client can decide to have access to just the name of persons, their employment status,
or the addresses of persons, or employers, or both. For example, when a client
chooses to activate the Address layer but not the Employment layer, address information
of persons will be printed in addition to their names. When the Employment layer is activated on top, a request for displaying a person object will result in printing
that person's name, its address, its employer, and its employer's address, in that
particular order. A code fragment showing the activation of these two layers is given
in Figure 5.
Note that layer activation affects the behavior of the entire program in the dynamic
extent of the with construct, not on selected objects. Furthermore, the code
in Figure 4 duplicates major parts of the code for classes Person and Employer.
However, this is for illustration purposes only since both classes can as well inherit a
common code base from a shared superclass, including shared implementations for
the different layers.
Figure 5: Direct layer activation.
Contrary to the examples discussed in previous publications about our work
on COP, this code example does not modularize the source code along the layers,
but keeps the object-oriented modularization along classes. In other words, instead
of textually grouping partial class definitions inside layers - which is similar to
grouping aspects or features within their own modules in AOP and FOP - the layer
definitions are textually grouped inside classes. This layer-in-class notation has
different trade-offs than the class-in-layer notation. One advantage is that layers can
refer to private fields of the core class definition, whereas in class-in-layer notations,
members that need to be referred to in other layers (aspects, features, etc.) cannot
be fully encapsulated. Another advantage is that new classes can be added to a
system offering their own layer-specific behavior without the need to change layer
definitions elsewhere.
Our example, as discussed here, uses simple print statements to display information
about objects, which in turn call the toString methods. In situations with
more advanced GUI presentations required, state changes need to initiate automatic
updates of such on-display presentations. In Section 5, we show how COP can be
beneficial in the implementation of display update behavior.
Environment-dependent Behavior Variations
In the previous example, the composition of behavioral variations is explicitly initiated
by actors using the with construct from within the control
ow of the program.
In the general case, however, activation or deactivation of layers may depend on
non-local contextual conditions of the environment. For example, whether address
information (or other kinds of information) is displayed may depend on the setting
of some menu entry in the client program, on a user's login status, whether a user
has sufficient access rights to view sensitive information, and so on. In general, any
dynamic condition can determine whether some layer should be activated or not.
The with construct is in principle already sufficient to express this: It can just
be guarded by an appropriate if statement. In Figure 6, this is shown for both
ContextJ and ContextS, our COP extension to Squeak/Smalltalk. The disadvantage
Figure 6: Conditional layer activation.
in this case, though, is that the code on which layers may need to be activated or
not must be duplicated for each branch (code sections 1 and 2 in Figure 6).
In ContextS we implemented an alternative approach to conditional layer activation:
The message useAsLayersFor: can be sent to a sequenceable collection that
contains the layers to be activated when evaluating the block passed as argument
to useAsLayersFor:. This property can be used to avoid code duplication in the
alternative branches of a guarding clause (code section 3 in Figure 6).
In principle, ContextJ can be designed to support first-class layers and computed
layer activation as well (see Appendix A). The solution in ContextS is remarkable,
though, in that Smalltalk lends itself to designing layers as first-class objects from
the start and that especially Smalltalk's elegant block construct makes syntactic
language extensions for layer activation and deactivation unnecessary.
This allows us to avoid explicit conditionals in general, and to use dedicated
computations that derive layer combinations appropriate for a particular execution
context. With that, context can be modelled as first-class objects that, for example,
can be used as shown in section 4 of Figure 6.
System-dependent Behavior Variations
To illustrate a COP-style implementation of system-dependent behavior variations,
we show a modified version of the figure editor code written in ContextJ [16], here
implemented in ContextL, our first fully implemented programming language extension for COP [14] built on top of the Common Lisp Object System (CLOS). The figure editor is a prominent example used in aspect-oriented software development
to motivate cflow-like constructs needed to deal with the phenomenon of jumping
aspects [11].
Figure 7: A layered implementation of the figure editor example.
In Figure 7, we see a layered class figure-element providing a simplified abstract
interface to graphical objects to be presented on the screen. The code also
defines a layer display that handles display updating on slot changes: Whenever
a layered slot is changed through an assignment, the reflective function layered-slot-set is called on the object whose slot is to be assigned, together
with a first-class function writer that performs the actual assignment when invoked.
The function layered-slot-set is overriden for figure-element to perform the
actual update of grapical objects on the screen (assumed to be implemented by the
function update-display, which is not detailed further in this paper).
Figure 7 also contains two example classes point and line that inherit from
figure-element. They define x- and y-coordinates, and two endpoints respectively,
together with specifications for implicit initialization arguments for constructors :initarg and accessor methods :accessor, which are standard slot options in
CLOS. ContextL adds the :layered option that indicates whether the respective
slot is layered or not. This allows fine-grained control over which slots are read and
written through reflective functions and allows expressing, in this example, whether
a change to a specific slot should trigger an update to the screen or not.
In the general case, graphical objects may be either primitive, like point, or
composites, like line, which consists of two endpoints. Usually every change to a
composite object, for example by calling move on a line instance, implies respective
changes to the primitive objects the composite combines. However, a call of a
top-level move should only cause a single notification after performing all implied
changes to the combined objects to avoid unnecessary and inaccurate intermediate
screen updates. To this end, both layered-slot-set and move are defined in
the layer display to first deactivate display itself for the dynamic scope of the
actual change of the figure element. In order to avoid code duplication, the common
code for layered-slot-set and move is factored out into a higher-order function call&update that expects a parameterless function for performing the update on an
object and the object itself. The around method for layered-slot-set in the layer display passes the writer parameter, and the around method for move in display passes the CLOS construct for super calls, call-next-method, as a function.
It is this deactivation of the layer display in call&update that is neither triggered
by an actor nor by dynamic conditions in the environment, but is internally
required by the system to coordinate display updating. Discussion
We have already introduced ContextL and a variation of ContextJ in previous publications
on COP. The examples given above summarize the examples discussed before
to illustrate COP as a more general concept, but also discuss new elements of the respective
languages. Notably: (a) We have shown ContextJ with an AOP/FOP-style
class-in-layer notation before, but this paper introduces the layer-in-class notation
for the first time. (b) ContextS is used here to illustrate an elegant way to deal
with layers as first-class objects. Layers as first-class objects are also available in
ContextL but have not been discussed before. (c) In the ContextL example shown
here, we discuss layered slots for the first time which allow for intercession of slot
accesses in layered methods.
These examples all show that the notion of layer activation and deactivation
is a useful concept of its own, independent of how the source code is structured
to define layer-specific behavior. Indeed, the essential contribution of COP is the
ability to refer to layers at runtime and activate or deactivate them in arbitrary
code locations. In other words, COP brings a similar degree of dynamicity to the
notion of crosscutting concerns that object-oriented programming brought to ad-hoc
polymorphism.
Figure 8: Layer activation from within a loop.
In this regard, it is especially interesting to compare COP to cflow-style constructs
from aspect-oriented programming. Cflow constructs, as introduced with
AspectJ-like languages, match join points within the dynamic extent of another join
point [29]. They allow for the expression of control-flow-dependent behavior variations
and, in conjunction with if pointcuts, the conditional composition of such
behavior variations. In this sense, AOP languages with flow constructs can already
be regarded as supporting a context-oriented programming style. However, AOP
has emerged from the ambition to textually modularize crosscutting concerns. In
this sense, the layer-in-class notation used in the ContextJ example above would not
qualify as AOP because it scatters layer-specific definitions in the classes to which
they belong.
Another important difference between cflow-style pointcuts in AOP and layer
activation/deactivation in COP is that COP allows the use of layer activation/deactivation in arbitrary places of the source code whereas pointcuts in AOP
can only trigger at join points as exposed by the rest of the program. For example,
consider the ContextJ example from above and assume that we want to print a list
of persons with their employers and the employers' addresses, but not addresses of
the persons themselves. In a COP style, we can write this down directly (Figure 8).
With cflow-style pointcuts, we would have to ensure that the relevant part of the
loop body is exposed as join points, for example by factoring it out into a separate
method or using statement annotations [18]. In both cases, the join points would
have to be exposed, which means that encapsulation boundaries are potentially
violated and that the join point interface has to be maintained for future versions
of the code due to the fragile pointcut problem [31].
In the figure editor example, a reflective hook is used for intercepting slot accesses.
This is modelled along the lines of, and actually in terms of, the similar
slot access protocol in the CLOS Metaobject Protocol [28]. This style is a natural fit for the typical higher-order programming styles which are traditionally used in
Lisp dialects to integrate crosscutting and non-functional concerns. This example
is shown here to illustrate further that the notion of dynamic layer activation and
deactivation is independent of other elements of programming style supported by a
given language.
Furthermore, the conditions for triggering updates in the figure editor example
continuously change at runtime. This requires efficient implementations from
both aspect-oriented-style cflow constructs as well as context-oriented-style layer activation and deactivation. We have previously shown how ContextL can be implemented
efficiently [16]. In aspect-oriented approaches, both static analysis [5]
and guards [10] show substantial improvements over naive checks of control flow
properties. The latter implementation strategy, as used in the newest version of
the Steamloom virtual machine, is a dynamic optimization and therefore especially
interesting for possible future COP implementations.
6 RELATED WORK
Aspect-oriented and Feature-oriented Programming Aspect-oriented programming
language extensions provide constructs for modularizing crosscutting concerns
[30]. A crosscutting concern is some program behavior, be it functional or
non-functional, that does not fit the dominant modularization of a program. For
example in object-oriented languages, the dominant modularization is based on a
class hierarchy where the only way to share state and behavior across several classes
is by way of inheritance. An aspect can define additional state and behavior across
several classes independent of the structure of the class hierarchy. An especially
interesting contribution of aspect-oriented programming are means to decrease code
scattering: The source code of a program exhibits code scattering when the same,
or similar, fragments of code are repeated throughout. Aspects can help to reduce
code scattering by abstracting away the places in a program where some code has
to be executed, and defining that code only once and in a single location.
Like AOP, feature-oriented programming [7] also targets crosscutting concerns.
For example, the mixin layers approach [37] models features as layers which consist
of partial class definitions, similar to the layers of Context-oriented Programming as
described in this paper. The approach taken in [4] is based on mixin layers that may
include constructs for defining AOP-style pointcuts and advice, showing that AOP
and FOP are not fundamentally incompatible. However, the focus of FOP is on
compile-time selection and combination of feature variations, and more recent tool
support incorporates algebraic means for reasoning about such feature combinations
to improve static analyzability [6].
Context-oriented Programming, as presented in this paper, is closer to FOP
than to AOP: It also takes the notion of layers and provides means for selecting and
combining them. However, the main difference between FOP and COP is that the
former focuses on compile-time selection and combination, whereas the latter adds
the notion of dynamic activation and deactivation of layers together with scoping
mechanisms to delimit their activity state.
Unlike AOP and FOP, COP does not require the textual modularization of crosscutting
concerns in the source code of a program. As illustrated in Section 5, the
behavioral variations may be placed in the source code by making them part of the
respective class definitions. However, it must be possible to unambiguously refer
to all the behavioral variations that belong to one layer. Otherwise, dynamic activation/deactivation of behavioral variations would not be feasible in a straightforward
way. It is exactly this possibility to refer to crosscutting behavioral variations
grouped as layers at runtime that is important for Context-oriented Programming.
Context-awareness The term Context-oriented Programming was first used to
refer to the notion of context-aware applications in pervasive and ubiquitous computing.
Early approaches focused on the modeling and provision of context information
[17]. While this is an important prerequisite for implementing context-aware
applications, Context-oriented Programming is concerned with programming language
constructs to represent and manipulate behavioral variations. The first precursors
to the generalized notion of Context-oriented Programming presented in this
paper were placed in the context of pervasive and ubiquitous computing [20, 27].
Dynamic Activation Programming languages that treat procedures or methods
as first-class values allow programs to be structured in a way that they can exhibit
different behavior under different circumstances. In pure functional programming
languages like Haskell, they can be passed as parameters to higher-order functions,
and in languages like Scheme or ML, they can be assigned to variables which can be
side-effected later on to change the behavior of a program. However, the availability
of first-class procedures alone does not offer sufficient means to coordinate changes
of several collaborating procedures.
First-class environments offer a way to group several variable bindings, which
can contain first-class procedures or functions as values, and allow code to be executed
in such environments or even manipulate their bindings. However, aside from
some implementations of Scheme and Lisp, essentially no mainstream programming
language provides first-class environments as a mechanism available to programmers.
Piccola [1] is an experimental language for specifying applications as compositions
of software components. A key feature of Piccola is the form - a first-class
environment which is used to model, amongst others, objects, components, modules
and dynamic contexts [2]. Although environments can be manipulated in Piccola,
expressions are statically bound to the environment they are evaluated in, so dynamic
activation of scopes is not directly supported.
Scoped Activation Dynamic scoping can be used to change the binding of variables
for the current execution context [22, 32, 39]. In languages with first-class
functions, the change of function bindings can also be dynamically scoped, but special
care has to be taken when diferent functional values for the same dynamically
scoped variable need to wrap each other [13]. Dynamically scoped functions, however,
still have the limitation that they do not offer explicit means to coordinate the
change of collaborating functions. An interesting application of scoped activation
of functions is described by Gabriel [19]. Local virtual functions, implemented as a
pre-processor for C++, provide a similar concept [23].
Several aspect-oriented approaches already provide scoped aspect activation as
abstractions [9, 24, 35, 40, 43], but these abstractions have foremostly been designed for aspect deployment. They are all suitable for Context-oriented Programming to
different extents. Recently, ContextL [16] and Steamloom [10] have shown that
scoped aspect/layer activation can be erfficiently implemented, an important prerequisite
for wider adoption. This paper shows that scoped layer activation is a language
construct that is independent from the textual organization of source code, be it into
aspect-oriented modules, feature-oriented layers or otherwise.
Other Related Work Context-oriented Programming combines layers, dynamic
activation based on context, and scoped activation. Different combinations of these
notions already exist, some of which are even quite old. The separation of programs
into layers is an idea that goes back at least to early experiments made in
Smalltalk [8, 21]. There, layers were conceived as a mechanism to express different
design alternatives of the same software, and allow the developer to try
different combinations thereof. Us [38], Delegation layers [34] and Slate [36] are
very close to COP in that they are based on layers, allow sending messages in
the scope of a specific layer, and even allow manual dynamic composition of layers.
The context-oriented approaches presented in this paper abstract away from
the need to explicitly compose layers and provide dedicated language constructs instead - with-active-layers and with-inactive-layers in ContextL, with and
without in ContextJ, and useAsLayersFor: in ContextS. These language abstractions
enable non-trivial and efficient implementations of the respective language
extensions [15, 16].
Changeboxes [33, 44] offer a further evolution of the notion of Classboxes. A
Changebox encapsulates a software change at a higher-level of abstraction than
Classboxes (which only record additions, deletions or modifications to methods).
Changeboxes can be composed to provide a runtime environment for software applications.
Different Changeboxes can be in effect at the same time within a running
application, and may be dynamically activated or deactivated, thus supporting a
form of COP. In the present prototype, activation is specified programmatically,
but implicit activation based on context is planned in the longer term.
7 OUTLOOK
Real software systems change over time, and must adapt to changing requirements
even while they are running. Unfortunately, mainstream programming languages
and development environments do not support this kind of dynamic change very well,
leading developers to implement complex designs that anticipate various dimensions
of variability.
We propose instead to develop a notion of Context-oriented Programming that
directly supports variability depending on a large range of dynamic attributes. In effect, runtime behavior can be dispatched on any properties of the execution context.
Our first prototypes have illustrated how COP supports multi-dimensional
dispatch to achieve expressive runtime variation in behavior.
More research and experimentation is clearly needed into different ways to compose
and trigger variations. For example, variations may be expressed not only
as differences in code, but as extensions, wrappers, advice, refactorings, or general
transformations. Variations may not only be triggered explicitly and programmatically,
but also implicitly by means of rules or constraints.
One compelling application domain for COP is to control software evolution.
COP can enable runtime deployment of software changes while strictly delimiting
the visibility of changes to specific clients and leaving others untouched. Radical
changes can slowly percolate through a running system, without breaking clients
which are not ready for them. Backwards-compatibility need no longer be a critical
concern if the client context is taken into account when deploying changes. Global
consistency is neither assumed nor desirable.
COP signals a move away from application-specific solutions to runtime variability
(such as those offered by many design patterns), and instead focuses on
developing a new programming paradigm and corresponding language constructs
and underlying software infrastructure to support context-dependent behavior. We
believe that these steps are essential to achieving the high degree of maintainability,
robustness and adaptability that is needed for the emerging breed of dynamic,
mobile and pervasive applications.
Implementations of ContextJ , ContextS, and ContextL can be downloaded from http://www.swa.hpi.uni-potsdam.de/cop/
A CONTEXTJ
In this section, we present an implementation of a subset of ContextJ which is
realized in plain Java. ContextJ as used throughout this paper would require an
extension of the Java programming language, together with a new compiler and
possibly an extension of the Java Virtual Machine. As a proof of concept, we focus
here on a subset of ContextJ that is necessary to support the example programs
presented in this paper. Furthermore, we require a few idioms to be followed in
client code that could otherwise be automatically generated in a proper ContextJ
compiler or preprocessor. An advantage of this approach is that the implementation
presented in this appendix can be run in a standard Java environment without any
extensions.2 To distinguish between ContextJ as presented in the previous sections
and ContextJ as implemented in this appendix, we refer to the latter as ContextJ.
Actor-dependent Behavior Variations in ContextJ
We introduce ContextJ by first showing a reimplementation of the example given
in Section 5 for actor-dependent behavior variations, depicted in Figure 9.
To support layered definitions in Java classes, a program has to create instances
of the ContextJ class Layer to represent layers as first-class objects (lines 5-8).
Each class that wants to support context-dependent bahavioral variations has to
provide a context interface for (at least) the methods that should behave differently
according to context (lines 12-14) and has to implement that context interface (line
21). Such a class has to define an object-specific container for context-dependent
layer definitions of the generic type LayerDefinitions, parameterized with the
previously defined context interface (lines 35-36). The methods that need to exhibit
context-dependent behavior have to forward calls to that container using the
container-specific method select (lines 38-40). This is always possible because select is guaranteed to return an object implementing the context interface on
which the container is parameterized.
A LayerDefinitions container supports two further methods define and next.
With define, a context-dependent implementation for a given layer can be defined
for the class at hand: It takes a layer instance { for example the ContextJ-defined RootLayer or any of the application-defined layers (here from lines 5-8) - and an
instance of another class implementing the respective context interface, typically in
the form of an anonymous class instance (for example lines 42-48). Such definitions
are conveniently provided in an initializer that runs as part of any constructor (lines
42-65). The next method of a LayerDefinitions container can be used to call
the next most specific method in a current set of active layers. In other words, the
idiom layers.next(this).someMethod(...) picks the next most specific layer
definition and calls the indicated method, similar to an invocation of proceed in
Figure 9: An implementation of the example from Figure 4 in ContextJ.
Figure 10: Direct layer activation in ContextJ.
ContextJ as presented earlier. Here, the method to be invoked will be the implicit
call to toString() (lines 53 and 61).
The idiomatic code that could be generated by a preprocessor consists of:
- the declaration of an instance variable that holds the container for layer definitions (lines 35-36),
- the forwarding calls to that container based on the context interface (lines 38-40),
- the calls to define in an initializer based on layer declarations (lines 42-65),
- and the idiom layers.next(this) based on calls to proceed (lines 53 and
61).
A code fragment showing the activation of the layers introduced in the example
above is shown in Figure 10 which produces the same result as the original code
in Figure 5. ContextJ provides the (global static) method with that takes any
number of Layer instances and returns an object that allows execution of a block
of code in a scope in which these layers are active, through the method eval.
An Implementation of ContextJ
An implementation of the ContextJ constructs used here is shown in Figure 11. It
consists of a class ContextJ that provides a number of static members that can be
conveniently used in any program via a static import. A layer is just an instance of an
empty class Layer (line 7), for example the RootLayer (line 9). The set of currently
Figure 11: An implementation of ContextJ in plain Java.
active layers is stored in a ThreadLocal private variable activeLayers that contains
only the RootLayer by default (lines 11-17). This variable is ThreadLocal to ensure
that different threads can have different sets of active layers without interfering with
each other.
An auxiliary interface Block is introduced to support execution of code blocks
for some context (lines 19-21).3 An auxiliary class WithEvaluator takes care of
handling layer activation and deactivation around the execution of a code block
(lines 23-37). It stores an array of layers to be activated in an instance variable layers (lines 24 and 26).
The method eval clones the set of currently active layers (line 30), and subsequently
activates each layer in the stored array of layers (lines 31-34). To this end,
each such layer is first removed from the set of currently active layers (line 32) and
then added to the front (line 33). The prior removal of a layer ensures that a layer is
never activated more than once, and the addition to the front ensures that the order
of active layers always respects the order of activation during program execution.
After layer activation, the code block passed as an argument to eval is executed,
and finally the set of active layers is restored to the previously cloned set (line 35).
The static method with takes any number of layers and returns an instance of WithEvaluator initialized with these layers.4
Finally, ContextJ provides a container type LayerDefinitions to be parameterized
with a context interface declaring the context-dependent methods (lines
43-75). This container maps layers to definitions in both directions, from layers to
definitions and from definitions to layers (lines 45-46). The method define adds
a layer/definition mapping to these two maps (lines 48-51). The method select iterates over the set of currently active layers (line 54), searches for the first layer
that maps to a definition and returns that definition (lines 55-56). If no mapping is
found, select returns null.
There are two versions of the method next (lines 61-70 and 72-74). One takes an
instance of the class Layer and searches for another layer that follows that instance
in the set of currently active layers (lines 63-64) and that maps to a definition (lines
65-68). (The search is implemented analogously to that of the method select.)
The other version of next takes an instance of the type parameter Definition,
picks the corresponding layer from the second map and calls the previous version of next with that layer (lines 72-74). The latter version of next is the one used in the
idiom layers.next(this) used for calling the next most specific method in the set
of currently active layers.
Please note the following:
- The return of null if no layer is found in the select and next methods appears
to be dangerous at first. However, RootLayer is always present by default in
the set of current active layers, should never be removed in a without construct
and should always be mapped to a definition in each context-dependent class.
All these requirements can be checked and ensured statically. In other words,
it should be straightforward to ensure that there is always a definition.5
- The search for definitions is not very efficient. However, we have already
shown how caches speed up method lookup in ContextL such that the overhead
becomes unnoticeable for non-trivial benchmarks [16]. See the related works
section of that paper for hints towards further optimization opportunities.
Conditional Layer Activation in ContextJ
As a final illustration of using ContextJ, we present the examples for conditional
layer activation from Figure 6 using ContextJ in Figure 12. Code section 1/2
repeats the approach in which the code on which layers may need to be activated
or not is guarded by an if statement. Code section 3 shows how the guard can
be inlined as a conditional expression that produces the correct set of layers to be
activated depending on context and passes that set of layers to with. Here we take
advantage of the fact that, as in ContextS, layers are first-class entities. The general
idiom is presented in code section 4 in Figure 12. 
Figure 12: Conditional layer activation examples from Figure 6 in ContextJ.
Acknowledgements
We thank Sven Apel, Nick Bourner, Johan Brichau, Thomas F. Burdick, Drew
Crampsie, Marcus Denker, Brecht Desmet, Stéphane Ducasse, Johan Fabry,
Richard P. Gabriel, Michael Haupt, Christian Heinlein, Andy Kellens, Bjoern Lindberg,
Martin von Löwis, Wolfgang De Meuter, Jim Newton, Andreas Raab, Andreas
Rasche, Christophe Rhodes, Dave Thomas, Jorge Vallejos, Matthias Wagner, Peter
J. Wasilko, JonL White, and Roel Wuyts for fruitful discussions and valuable
contributions.
Footnotes
1 Please note that ContexJ is not yet implemented. In Appendix A we provide a library-based
implementation of a subset of ContextJ called ContextJ.
2 The code presented in Appendix A has been tested with JDK 1.5.0.
3 This is similar to the standard Runnable interface as used in Java's multithreading support.
4 A similar pair of definitions for layer deactivation WithoutEvaluator and without can be
implemented anologously, but is left out here to save space.
5 A proof of soundness is future work, though.
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About the authors
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Robert Hirschfeld is a Professor of Computer Science at the
Hasso-Plattner-Institut (HPI) at the University of Potsdam. He received
a Ph.D. in Computer Science form the Technical University
of Ilmenau, Germany. He can be reached at hirschfeld@hpi.unipotsdam.de. See also http://www.swa.hpi.uni-potsdam.de/. |
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Pascal Costanza has a Ph.D. degree from the University of Bonn,
Germany, and works as a research assistant at the Programming
Technology Lab (Prog) of the Vrije Universiteit Brussel, Belgium.
He can be reached at pascal.costanza@vub.ac.be. See also http://pcos.net.
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Oscar Nierstrasz is a Professor of Computer Science at the Institute
of Computer Science (IAM) of the University of Bern. He
completed his B.Math at the University of Waterloo in 1979 and
his M.Sc. in 1981 and his Ph.D. in 1984 at the University of
Toronto. He can be reached at oscar.nierstrasz@acm.org. See also
http://www.iam.unibe.ch/~oscar.
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Cite this article as follows: Robert Hirschfeld, Pascal Costanza, Oscar Nierstrasz: "Context-oriented Programming", in Journal of Object Technology, vol. 7, no. 3, March-April 2008, pp. 125-151, http://www.jot.fm/issues/issue_2008_03/article4/.
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