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An overview of AspectJ


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AspectJ™ is a simple and practical aspect-oriented extension to Java.. With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ’s dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.
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An Overview of AspectJ
Gregor Kiczales
, Erik Hilsdale
Jim Hugunin
Mik Kersten
Jeffrey Palm
and William G. Griswold
Department of Computer Science, University of British Columbia,
201-2366 Main Mall, Vancouver, BC V6T 1Z4 Canada
Xerox Palo Alto Research Center
3333 Coyote Hill Road, Palo Alto, CA 94304 USA
(hilsdale, hugunin, mkersten, palm)
Department of Computer Science and Engineering, University of California, San Diego
La Jolla, CA 92093 USA
Abstract. AspectJ™ is a simple and practical aspect-oriented extension to
Java™. With just a few new constructs, AspectJ provides support for modular
implementation of a range of crosscutting concerns. In AspectJ’s dynamic join
point model, join points are well-defined points in the execution of the
program; pointcuts are collections of join points; advice are special method-like
constructs that can be attached to pointcuts; and aspects are modular units of
crosscutting implementation, comprising pointcuts, advice, and ordinary Java
member declarations. AspectJ code is compiled into standard Java bytecode.
Simple extensions to existing Java development environments make it possible
to browse the crosscutting structure of aspects in the same kind of way as one
browses the inheritance structure of classes. Several examples show that
AspectJ is powerful, and that programs written using it are easy to understand.
1 Introduction
Aspect-oriented programming (AOP) [14] has been proposed as a technique for
improving separation of concerns in software.
AOP builds on previous technologies,
including procedural programming and object-oriented programming, that have
already made significant improvements in software modularity.
The central idea of AOP is that while the hierarchical modularity mechanisms of
object-oriented languages are extremely useful, they are inherently unable to
modularize all concerns of interest in complex systems. Instead, we believe that in the
When we say “separation of concerns” we mean the idea that it should be possible to work
with the design or implementation of a system in the natural units of concern – concept, goal,
team structure etc. – rather than in units imposed on us by the tools we are using. We would
like the modularity of a system to reflect the way “we want to think about it” rather than the
way the language or other tools force us to think about it. In software, Parnas is generally
credited with this idea
[29, 30].
implementation of any complex system, there will be concerns that inherently
crosscut the natural modularity of the rest of the implementation.
AOP does for crosscutting concerns what OOP has done for object encapsulation
and inheritance—it provides language mechanisms that explicitly capture crosscutting
structure. This makes it possible to program crosscutting concerns in a modular way,
and achieve the usual benefits of improved modularity: simpler code that is easier to
develop and maintain, and that has greater potential for reuse. We call a well-
modularized crosscutting concern an aspect.
An example of how such an aspect
crosscuts classes is shown in Figure 1.
AspectJ is a simple and practical aspect-oriented extension to Java. This paper
presents an overview of AspectJ, including a number of core language features, the
basic compilation strategy, the development environment support, and several
examples of how AspectJ can be used.
The examples show that using AspectJ we can
code, in clear form, crosscutting concerns that would otherwise lead to tangled code.
The main elements of the language design are now fairly stable, but the AspectJ
project is not nearly finished. We continue fine-tuning parts of the language, building
a third-generation compiler, expanding the integrated development environment
(IDE) support, extending the documentation and training material, and building up the
user community. We plan to work with that user community to empirically study the
practical value of AOP.
The next section describes the basic assumptions behind the AspectJ language
design. Section 3 presents the core language. Section 4 outlines the compiler.
Section 5 describes the AspectJ-aware tool extensions we have developed. Section 6
shows that AspectJ can capture crosscutting structure in elegant and easy to
understand ways. We conclude with a discussion of related and future work. As an
overview, detailed design rationale and detailed compiler and tool implementation
issues are outside the scope of this paper.
2 Basic Design Assumptions
AspectJ is the basis for an empirical assessment of aspect-oriented programming. We
want to know what happens when a real user community uses an AOP language.
What kinds of aspects do they write? Can they understand each other’s code? What
kinds of idioms and patterns emerge? What kinds of style guidelines do they
develop? How effectively can they work with crosscutting modularity? And, above
all, do they develop code that is more modular, more reusable, and easier to develop
and maintain?
Because these are our goals, designing and implementing AspectJ is really just part
of the project. We must also develop and support a substantial user community. To
AOP support can be added to languages that are not object-oriented. The key property of an
AOP language is that it provides crosscutting modularity mechanisms. So when we add AOP
to an OO language, we add constructs that crosscut the hierarchical modularity of OO
programs. If we add AOP to a procedural language, we must add constructs that crosscut the
block structure of procedural programs
[4, 6].
This paper is written to correspond with AspectJ version 0.8.
make this possible, we have chosen to design AspectJ as a compatible extension to
Java so that it will facilitate adoption by current Java programmers. By compatible we
mean four things:
Upward compatibility — all legal Java programs must be legal AspectJ programs.
Platform compatibility — all legal AspectJ programs must run on standard Java
virtual machines.
Tool compatibility — it must be possible to extend existing tools to support
AspectJ in a natural way; this includes IDEs, documentation tools, and design
Programmer compatibility — Programming with AspectJ must feel like a natural
extension of programming with Java.
The programmer compatibility goal has been responsible for much of the feel of the
language. Whereas our previous AOP languages were domain-specific, AspectJ is a
general-purpose language like Java. AspectJ also has a more Java-like balance
between declarative and imperative constructs. AspectJ is statically typed, and uses
Java’s static type system. In AspectJ programs we use classes for traditional class-like
modularity structure, and then use aspects for concerns that crosscut the class
There are several potentially valuable AOP research goals that AspectJ is not
intended to meet. It is not intended to be a “clean-room” incarnation of AOP ideas, a
formal AOP calculus or an aggressive effort to explore the AOP language space.
Instead, AspectJ is intended to be a practical AOP language that provides, in a Java
compatible package, a solid and well-worked-out set of AOP features.
3 The Language
AspectJ extends Java with support for two kinds of crosscutting implementation. The
first makes it possible to define additional implementation to run at certain well-
defined points in the execution of the program. We call this the dynamic crosscutting
mechanism. The second makes it possible to define new operations on existing types.
We call this static crosscutting because it affects the static type signature of the
program. This paper only presents dynamic crosscutting.
Dynamic crosscutting in AspectJ is based on a small but powerful set of constructs.
Join points are well-defined points in the execution of the program; pointcuts are a
means of referring to collections of join points and certain values at those join points;
advice are method-like constructs used to define additional behavior at join points;
and aspects are units of modular crosscutting implementation, composed of pointcuts,
advice, and ordinary Java member declarations.
This section of the paper presents the main elements of the dynamic crosscutting
support in the language. The presentation is informal and example-based.
Fig. 1. UML description of a simple figure editor. The box labeled “MoveTracking” shows an
aspect that crosscuts methods in the Point and Line classes. This aspect is discussed in detail in
Section 3
3.1 Join Point Model
The join point model is a critical element in the design of any aspect-oriented
language mechanism. This model provides the common frame of reference that makes
it possible for execution of a program’s aspect and non-aspect code to be properly
In previous work, we have used several different kinds of join point model,
including primitive application nodes in a dataflow graph [13, 18, 23, 27] and method
bodies [27, 28]. Early versions of AspectJ used a model in which the join points were
principled places in the source code.
The dynamic crosscutting elements of AspectJ are now based on a model in which
join points are certain well-defined points in the execution of the program. This model
gives us important additional expressive power, discussed in Section 3.9. In this
model join points can be considered as nodes in a simple runtime object call graph.
These nodes include points at which an object receives a method call and points at
which a field of an object is referenced. The edges are control flow relations between
the nodes. In this model control passes through each join point twice, once on the way
in to the sub-computation rooted at the join point, and once on the way back out.
We illustrate join points using a simple figure editor, the kernel of which is shown
in Figure 1, and which also serves as a running example. (Complete code from the
paper is at Based on these classes, executing the
first three lines of code in Figure 2 builds the objects shown below. In this picture
large circles represent objects, square boxes represent methods and small numbered
circles represent join points. Executing the last line starts a computation that proceeds
through the join points labeled below. In each case the join point is first reached just
before the action described begins executing. Control passes back through the join
point when the action described returns.
getX(): int
getY(): int
incrXY(int, int)
getX(): int
getY(): int
incrXY(int, int)
incrXY(int, int)
getX(): int
getY(): int
incrXY(int, int)
getX(): int
getY(): int
incrXY(int, int)
incrXY(int, int)
1. A method call join point corresponding to the incrXY method being called on the
object ln1.
2. A method call reception join point at which ln1 receives the incrXY call.
3. A method execution join point at which the particular incrXY method defined in
the class Line begins executing.
4. A field get join point where the _p1 field of ln1 is read.
5. A method call join point at which the incrXY method is called on the object pt1.
8. A method call join point at which the getX method is called on the object pt1.
11. A field get join point where the _x field of point pt1 is read.
Control returns back through join points 11, 10, 9 and 8.
12. A method call join point at which the setX method is called on p1.
… and so on, until control finally returns back through 3, 2 and 1
The different kinds of join points provided by AspectJ are shown in Table 1. Note
that while AspectJ defines a number of kinds of join points, only a few kinds suffice
for many programs, and all kinds of join points behave the same with respect to other
Point pt1 = new Point(0, 0);
Point pt2 = new Point(4, 4);
Line ln1 = new Line(pt1, pt2);
ln1.incrXY(3, 6);
Fig. 2. The first three lines of code build the objects shown as large circles below. The
rectangles represent methods.Executing the final line of code starts a computation tha
includes the sequence of join points shown as small numbered circles.
language features.
This substantially reduces the complexity of learning to program
with AspectJ.
3.2 Pointcut Designators
A pointcut is a set of join points, plus, optionally, some of the values in the execution
context of those join points. AspectJ includes several primitive
pointcut designators.
Programmers can compose these to define anonymous or named user-defined pointcut
designators. Pointcuts are not higher order, nor are pointcut designators parametric.
There is one exception to this rule. It is not possible to define before or around advice
on constructor reception or constructor execution join points.
Table 1. The dynamic join points of AspectJ. Join points marked with
are not used in further
examples in this paper.
kind of join point points in the program execution at which…
method call
constructor call
a method (or a constructor of a class) is called.
Call join points are in the calling object, or in
no object if the call is from a static method.
method call reception
constructor call reception
an object receives a method or constructor call.
Reception join points are before method or
constructor dispatch, i.e. they happen inside the
called object, at a point in the control flow after
control has been transferred to the called object,
but before any particular method/constructor
has been called.
method execution
constructor execution
an individual method or constructor is invoked.
field get a field of an object, class or interface is read.
field set a field of an object or class is set.
exception handler execution
an exception handler is invoked.
class initialization
static initializers for a class, if any, are run.
object initialization
when the dynamic initializers for a class, if any,
are run during object creation.
A simple way to think of pointcut designators is in terms of matching certain join
points at runtime. For example, the pointcut designator
receptions(void Point.setX(int))
matches all method call reception join points at which the Java signature of the
method call is
void Point.setX(int) Intuitively, this refers to every time a
point receives a call to change its
x coordinate. Similarly
receptions(void FigureElement.incrXY(int, int))
intuitively refers to every time any kind of figure element (i.e. an instance of Point
Line) receives a call to shift a certain distance.
Pointcuts can be combined using and, or and not operators (‘
&&’, ‘||’ and!’).
The following compound pointcut designator refers to all receptions of calls to a
Point to change its x or y coordinate.
receptions(void Point.setX(int)) ||
receptions(void Point.setY(int))
Primitive Pointcut Designators
AspectJ includes a variety of primitive pointcut designators that identify join points in
different ways. Some primitive pointcut designators only identify pointcuts of one
kind, for example
receptions only matches method call reception join points.
Others match any kind of join points at which a certain property holds. For example,
instanceof(Point) matches all join points at which the currently executing
object (the value of
this) is an instance of Point or a subclass of Point.
These two kinds of join point designators can be combined to identify join points
in useful ways. For example:
!instanceof(FigureElement) &&
calls(void FigureElement.incrXY(int, int))
matches all method calls to incrXY that do not come from an object that is a figure
element. This will mean calls that come from an object of another type, as well as
calls that come from static methods.
The primitive pointcut designators are summarized in Table 2. They are explained
further as they are used in the paper.
Because there is no currently executing object in static methods, the
instanceof(FigureElement) will not match such join points.
Table 2. Primitive pointcut designators. AnyTypeName position does normal sub-type
matching. Anyid position does matching by string equality. See section 3.9 for information
about more sophisticated wild card matching in these positions
Matches call/reception/execution join points at which the method or constructor
called matches
signature. The syntax of a method signature is:
ResultTypeName RecvrTypeName.meth_id(ParamTypeName,…)
The syntax of a constructor signature is:,…)
Matches field get/set join points at which the field accessed matches the signature.
The syntax of a field signature is:
FieldTypeName ObjectTypeName.field_id
Matches exception handler execution join points of the specified type.
Matches join points of any kind at which the currently executing:
- object is of type
- code is contained within
- code is contained within the member defined by the method or constructor
Matches join points of any kind that occur strictly within the dynamic extent of any
join point matched by pointcut_designator.
Matches method call join points that in one step lead to any reception or execution
join points matched by pointcut_designator.
Matches class or object initializations of the specified type.
User-defined Pointcut Designators.
User-defined pointcut designators are defined with the pointcut declaration. The
pointcut moves():
receptions(void FigureElement.incrXY(int, int)) ||
receptions(void Line.setP1(Point)) ||
receptions(void Line.setP2(Point)) ||
receptions(void Point.setX(int)) ||
receptions(void Point.setY(int));
defines a new pointcut designator, moves(), that identifies whenever a figure
element receives a call of a method that can move it. User-defined pointcut
designators can be used wherever a pointcut designator can appear.
3.3 Advice
Advice is a method-like mechanism used to declare that certain code should execute
at each of the join points in a pointcut. AspectJ supports
before, after, and around
advice. Additionally, there are two special cases of after advice, after returning and
after throwing, corresponding to the two ways a sub-computation can return through a
join point. Both before advice and all three kinds of after advice are strictly additive
with respect to the normal computation at the join point. Around advice has the
special capability of selectively preempting the normal computation at the join point.
This advice framework is based on the declarative method combination mechanism in
CLOS [11] (which itself was modeled on the demon methods of Flavors [8, 10, 31]).
Advice declarations define advice by associating a code body with a pointcut, and
a time, relative to each join point in the pointcut, when the code should be executed.
The advice declaration
after(): moves() {
flag = true;
defines after advice on the pointcut moves(). The ‘() betweenafter’ and the
:’ means the advice has no parameters. The effect of this declaration is to ensure that
flag variable is set to true whenever a figure element finishes handling a move
method call. (The declaration of the variable is shown in the example in Section 3.4.)
A simple model for the behavior of advice is in terms of runtime dispatch. (Section
4 outlines the techniques the compiler uses to ensure that most if not all of the
matching overhead happens at compile time.) Upon arrival at a join point, all advice
in the system are examined to see whether any apply at the join point. Any that do are
collected, ordered according to specificity (described in Section 3.5), and executed as
1. First, any around advice are run, most-specific first. Within the body of an
around advice, calling
proceed() invokes the next most specific piece of
around advice, or, if no around advice remain, goes to the next step.
2. Then all
before advice are run, most-specific first.
3. Then the computation associated with the join point proceeds.
4. Execution of
after returning and after throwing advice depends on
how the computation in step 3 and prior
after returning and after
advice terminate.
If they terminate normally, all after returning advice are run, least
specific first.
If they terminate by throwing an exception, all after throwing advice that
match the exception are run, least specific first. (This means
advice can handle exceptions thrown by less specific after
and after throwing advice.)
5. Then all
after advice are run, least-specific first.
6. Once all
after advice have run, the return value from step 3, if any, is returned to
the innermost call to proceed from step 1, and that piece of
around advice
continues running.
7. When the innermost piece of
around advice returns, it returns to the surrounding
around advice.
8. When the outermost piece of
around advice returns, control continues back from
the join point.
3.4 Aspects
Aspects are modular units of crosscutting implementation. Aspects are defined by
aspect declarations, which have a form similar to that of class declarations. Aspect
declarations may include pointcut declarations, advice declarations, as well as all
other kinds of declarations permitted in class declarations.
The following declaration defines an aspect that implements the behavior of
keeping track of whether a figure element has moved recently. This aspect might be
used by the screen update mechanism to find out whether anything has changed since
the last time the screen was updated. (More sophisticated versions of this aspect will
be presented as the paper proceeds.)
aspect MoveTracking {
static boolean flag = false;
static boolean testAndClear() {
boolean result = flag;
flag = false;
return result;
pointcut moves():
receptions(void FigureElement.incrXY(int, int)) ||
receptions(void Line.setP1(Point)) ||
receptions(void Line.setP2(Point)) ||
receptions(void Point.setX(int)) ||
receptions(void Point.setY(int));
after(): moves() {
flag = true;
Advice of an aspect are similar to methods in that they have access to all members of
the class. So in this case the after advice can reference the static variable
Aspect Instances
In AspectJ, the default behavior of non-abstract aspects is to have a single instance.
Advice run in the context of this instance. The
aspect declaration accepts a
modifier, called ‘
of’ that provides other kinds of aspect instance behavior.
Discussion of this functionality is outside the scope of this paper.
3.5 Aspect Precedence
In general, more than one piece of advice may apply at a join point. The different
advice can come from different aspects or even the same aspect. The relative order in
which such advice executes is well defined. The ordering is based on the fact that
aspects are the primary units of crosscutting functionality. So advice ordering, or
specificity, is resolved with respect to the relative precedence of the aspects in which
the advice is defined.
For two pieces of advice, a
and a
, defined in aspects A
and A
respectively, the
relative specificity is determined as follows:
If A
and A
are the same, whichever piece of advice appears first in that aspect
declaration’s body is more specific. This rule exists because one aspect may need
to define multiple advice that apply at the same join point. This commonly
happens when there are matching before and after advice, but it can also happen
with two pieces of advice of the same kind.
If A
directly or indirectly extends A
, then a
is more specific than a
. This rule is
a natural extension of method overriding rules in OO languages. It supports the
common case where the related advice are defined in aspects that naturally exist
in an extends relationship. (Section 3.8 discusses aspect inheritance and
overriding in more detail.)
If the declaration of A
includes a dominates modifier that mentions A
, then a
is more specific than a
. This rule exists because, in some cases, the programmer
needs to control precedence between aspects that do not exist in an extends
In all other cases the relative specificity between a
and a
is undefined.
This is the most common case – two conceptually and semantically independent
aspects define advice that apply at the same join point – and the programmer does
not need to control the relative ordering of such advice.
The following mobility aspect is an example of the use of the
dominates modifier.
This simple aspect implements a global flag that freezes all figure elements so that
they cannot move. The aspect works by checking the flag before any move operation,
and simply doing a “quiet abort” of the operation if moves are disabled.
aspect Mobility dominates MoveTracking {
private static boolean enableMoves = true;
static void enableMoves() { enableMoves = true; }
static void disableMoves() { enableMoves = false; }
around() returns void: MoveTracking.moves() {
if ( enableMoves ) {
It would not make sense for this aspect to extend MoveTracking, because it
doesn’t define a more specialized version of the move tracking functionality. But it is
essential that it have precedence over
MoveTracking, so that it can abort a move
before it gets registered. Note that the code for this aspect shows that one aspect can
refer to a pointcut defined in another aspect in the same way that static fields are
referred to in Java.
3.6 Pointcut Parameters
In many cases it is useful for advice to have access to certain values that are in the
execution context of the join points. For example, a more sophisticated version of the
move tracking aspect might record the specific figure elements that have moved
recently rather than just a single bit saying that some figure element has moved
AspectJ provides a parameter mechanism that makes it possible for advice to see a
subset of the values in the execution context of join points. This mechanism operates
in both advice and pointcut declarations. In advice declarations values can be passed
from the pointcut designator to the advice. In pointcut declarations values can be
passed from the constituent pointcut designators to the user-defined pointcut
designator. In both cases, the flow of values is from the right of the ‘
:’ to the left.
The net effect is that values made available by primitive pointcut designators can be
used in the body of advice.
For example, the following piece of advice has access to both the object receiving
the method call and the argument to that call:
before(Point p, int nval):
receptions(void p.setX(nval)) {
System.out.println(“x value of”+p+
“ will be set to ” + nval + “.”);
The parameter mechanism uses a combination of positional and by-name matching.
The list of parameters to the left of the ‘
:’ declares that this piece of advice has two
parameters, of type Point and int, named p and nval respectively. Then, to the
right of the colon, those two parameter names can be used in the same position that a
type name would normally appear to say that the parameter should get the
corresponding value. So, the
p and nval in p.setX(nval) mean that the effective
signature is Point.setX(int), and that p should get the object receiving the call,
nval should get the value of the first argument to the call.
Definition and use of parameters works in a similar way in user-defined pointcuts.
In this code
pointcut incrXYs(FigureElement fe):
receptions(void fe.incrXY(int, int));
after(FigureElement figElt): incrXYs(figElt) {
<‘figElt’ is bound to the figure element here>
the pointcut declaration says that incrXYs(FigureElement) exposes a single
parameter, of type
FigureElement, and that it is the receiver of the incrXY
method call. The advice declaration says that
figElt should be bound to the first
parameter of
incrXYs, which is the figure element being moved. Note that the name
of the parameter in the pointcut declaration does not have to be the same as within the
advice declaration.
Values can be exposed from other primitive pointcut designators as well. A
common case is to use
instanceof with a parameter to provide access to the object
making a call, as follows:
pointcut gets(Object caller):
instanceof(caller) &&
(calls(int Point.getX()) ||
calls(int Point.getY()) ||
calls(Point Line.getP1()) ||
calls(Point Line.getP2()));
The primitive pointcut designators expose values as suggested by the naming
convention in Table 2. The
RecvrTypeName position in method signatures exposes
the object receiving the method call and so on.
Static Typing of Receiver
In a highly polymorphic pointcut designator like moves, there is no common super
type that accepts all of the method calls in the pointcut (i.e. there is no type that
accepts all of
incrXY, setP1, setP2, setX and setY). That means it isn’t
possible to write
moves to expose the figure element that is moving by simply
plugging a common parameter into the receiver position of each receptions. One
cannot write something like:
pointcut moves(FigureElement fe):
receptions(void fe.incrXY(int, int)) ||
receptions(void fe.setP1(Point)) ||
receptions(void fe.setP2(Point)) ||
because setP1 is not defined on FigureElement. Instead, the object receiving
the calls must be picked up using
instanceof as follows:
pointcut moves(FigureElement fe):
instanceof(fe) &&
(receptions(void FigureElement.incrXY(int, int)) ||
receptions(void Line.setP1(Point)) ||
receptions(void Line.setP2(Point)) ||
receptions(void Point.setX(int)) ||
receptions(void Point.setY(int)));
Access to Return Values
In some cases, after returning advice may want to access the value being
returned through the join point. This is done with special syntax, to make it clear that
the return value is only present in after returning advice:
after(Point p) returning (int x):
receptions(int p.getX()) {
System.out.println(p + “ returned ” +
x + “ from getX().”);
Parameters and proceed
Within an around advice that has parameters, proceed accepts parameters with
the same signature as the
around advice itself. Calling proceed with different
actual values for those parameters will cause all remaining advice and the rest of the
computation to see the new values. This can be used to implement advice that does
pre-processing on the values as follows:
around(int nv) returns void:
receptions(void Point.setX(nv)) ||
receptions(void Point.setY(nv)) {
proceed(Math.max(0, nv));
The effect of this advice is to ensure that any method call to change the x or y
coordinate of a point has its parameter clipped to greater than zero before the change
3.7 Reflective Access to Join Point
To make certain kinds of advice easier to write, AspectJ provides simple reflective
access to information about the current join point. Within the body of an advice
declaration, the special variable
thisJoinPoint is bound to an object representing
the current join point. The join point object provides information common to all join
points, such as what kind of join point it is and the signature of the surrounding
method. It also provides information specific to each kind of join point, i.e. a field
reference join point provides access to the field signature.
3.8 Inheritance and Overriding of Advice and Pointcuts
To support aspect-libraries, AspectJ provides a simple mechanism of pointcut
overriding and advice inheritance. To use this mechanism a programmer defines an
abstract aspect, with one or more abstract pointcuts, and with advice on the
pointcut(s). This, then, is a kind of library aspect that can be parameterized by aspects
that extend it. For example, the following defines a simple library of tracing
abstract aspect SimpleTracing {
abstract pointcut tracePoints();
before(): tracePoints() {
printMessage(“Entering”, thisJoinPoint);
after(): tracePoints() {
printMessage(“Exiting”, thisJoinPoint);
void printMessage(String when, JoinPoint tjp) {
code to print an informative message
using information from the join point
Using the library aspect in a specific situation just requires extending the aspect
and supplying a concrete definition for the abstract pointcut.
aspect IncrXYTracing extends SimpleTracing {
pointcut tracePoints():
receptions(void FigureElement.incrXY(int, int));
Making the abstract pointcut concrete in the sub-aspect has the effect of inheriting the
advice declaration from the super-aspect into the sub-aspect. If the sub-aspect
includes a
dominates modifier, that modifier affects the precedence of the inherited
3.9 Property-Based Crosscutting
The pointcuts presented above are all defined in terms of an explicit enumeration of
method signatures. Although this is appropriate in many cases, we have found that it
is useful to be able to define a pointcut by means of certain other properties of join
points. To enable such property-based crosscutting, AspectJ includes two kinds of
features, wildcarding in pointcut designators and control-flow based pointcut
Wildcarding in Pointcut Designators. AspectJ includes a very simple wildcarding
mechanism in pointcut designators. Examples of what this mechanism allows the
programmer to say are:
receptions(* Point.*(..))
matches receptions of calls to any method defined on the class Point (i.e.
incrXY(int, int), getX(), getY(), setX(int), setY(int)).
matches receptions of calls to any constructor for an object of type Point (i.e. the
Point(int, int) constructor).
receptions(public **.*(..))
matches receptions of calls to any public method defined on any type in the package.
receptions(* Point.get*())
matches receptions of calls to any method defined on Point for which the the id
starts with get and which accepts zero arguments – i.e. the nullary getters getX()
Control-Flow Based Crosscutting. AspectJ also includes two primitive pointcut
designators that allow picking out join points based on whether they are in a particular
control-flow relationship with other join points. In order to do this, these designators
differ from others in that they accept pointcut designators as parameters.
The cflow(pcd) pointcut designator matches all join points that are strictly
within the dynamic extent of the join points matched by
pcd. The points matched by
pcd itself are not matched by cflow(pcd). A canonical use of cflow is to
distinguish between top-level versus recursive calls of a method. So, for example,
pointcut moves(FigureElement fe): <as above>;
pointcut topLevelMoves(FigureElement fe):
moves(fe) && !cflow(moves(FigureElement));
This will also match calls to methods defined in the class Object. If the programmer
explicitly wants to exclude these they could write:
receptions(* Point.*(..)) &&
!receptions(* Object.*(..))
The definition of topLevelMoves reads as any join point matched by moves, but
not within the control flow of
moves. In other words, if the move operation invokes
another move operation recursively, that recursive operation will not be matched.
4 Implementation
This section briefly outlines the current language implementation.
The main work of any AOP language implementation is to ensure that aspect and
non-aspect code run together in a properly coordinated fashion. This coordination
process is called
aspect weaving and involves making sure that applicable advice runs
at the appropriate join points. As is the case with most other language features, aspect
weaving can be done by a special pre-processor [7], during compilation, by a post-
compile processor [14], at load time, as part of the virtual machine, using residual
runtime instructions, or using some combination of these approaches.
The AspectJ language design strives to be silent on the issue of when aspect
weaving should be done. We provide a compiler-based implementation of the
language that does almost all weaving work at compile-time. This exposes as many
programming errors as possible at compile time and avoids unnecessary runtime
overhead. Certain special cases of advice involve residual dispatch overhead at
The compiler uses a pay-as-you-go implementation strategy. Any parts of the
program that are unaffected by advice are compiled just as they would be by a
standard Java compiler.
The compiler transforms the source program in three ways: the body of every
advice declaration is compiled into a standard method, parts of the program where
advice applies are transformed to insert static points corresponding to the dynamic
join points, and code to implement any residual dynamic dispatch is inserted at those
static points.
4.1 Compilation of Advice Bodies
Every before or after advice body is compiled into a standard method and the advice
is run by a call to the method from appropriate points in the code. This potentially
means that the use of advice will add the overhead of a single method-call. But, these
methods are always either static or final, so they can easily be inlined by most JVMs
[11]. This means there should generally be no observable performance overhead from
these additional method calls.
An around advice body is compiled into one method body for each corresponding
static point in the code. This allows us to pass the needed state for the around
efficiently on the call-stack and to implement the
proceed statement without
needing to use Java’s reflection mechanisms. This implementation strategy trades an
increase in bytecode size for significantly reduced runtime overhead.
4.2 Corresponding Method
The compiler transforms the source program into a form in which there is an explicit
corresponding method for each dynamic join point that might have advice at runtime.
This transformation is only performed for join points that might have advice, not all
join points. So, for example, in a program that has advice on the pointcut designated
gets(int Point._x), the compiler would transform references of the form
p._x, where p is a Point, to Point.$jp$0$(p), and add the following method
to the class
private static int $jp$0(Point obj) {
return obj._x;
Once this corresponding method has been generated, before and after advice
are implemented by making the corresponding method call the advice methods, as
There are many cases, including this one, where the compiler will add additional
method calls in order to create corresponding methods. This happens for method call,
method call reception and field access join points. Extra method calls are also added
as part of the implementation strategy for around advice. The overhead of these
methods is small in any JVM, and again since they are all static or final, they will be
optimized away by good JVMs. We expect a future version of the AspectJ compiler to
provide optimizing modes that will eliminate some of these minor overheads.
4.3 Dynamic Dispatch
The use of certain pointcut designators, like cflow, callsto, and
instanceof, can require a run-time test to determine whether a particular
corresponding method actually matches a particular join point designator. In such
cases, the corresponding method includes residual testing code that guards the
execution of the advice. This overhead is relatively small.
5 Tool Support
In object-oriented programming, development tools typically allow the programmer
to easily browse the class structure of their programs. Such support enables the
programmer to see the inheritance and overriding structure in their program, as well
as seeing compact representations of the contents of individual classes [13, 18, 23].
For AspectJ, we are developing analogous support for browsing aspect structure.
This enables the programmer to see the crosscutting structure in their programs. It
works by showing a bi-directional coupling between aspects (and their advice), and
the classes (and their members) that the advice affect. Figure 3 shows one of the
extensions we have made to JBuilder 4. This extension to the structure view tool
allows the programmer to easily see a summary of all the crosscutting affecting the
class Point. If the structure view window is focused on an aspect, it will show all the
targets of that aspect’s advice.
A second kind of environment extension provides a more light-weight reminder of
the aspect structure. This extension works by annotating the source code, as seen in
the editor, with an indication of whether aspects crosscut that code. Figure 4 shows
how we have extended emacs with this functionality. The automatically generated
annotations name the aspects that crosscut the method. A keystroke command can be
used to pop up a menu of the advice, choose one, and jump to it.
We currently support AspectJ-aware extensions to emacs, JBuilder and Forte for
Java. Additional tool support includes debugger extensions to understand that advice,
display it correctly on the stack etc., as well as extensions to Javadoc [17] to make it
understand crosscutting structure and generate appropriate hyper-links etc.
Fig. 3. A portion of the screen when using the AJDE extension to JBuilder 4. The main
window on the right shows the code for the class
Point. The structure view on the left
shows the class
Point, and shows that setX, setY and incrXY are all crosscut b
advice; setX is further expanded to show what advice crosscuts it. The user can click on the
advice to
All of these extensions work by consulting a database that is maintained by the
compiler. Once the API stabilizes, we intend to make it public so that others can
develop tools that use it as well.
6 Understanding Crosscutting Structure
One of the most important questions we must answer is how easy is it to program
with AspectJ. In particular, is crosscutting structure, implemented with AspectJ,
something that appears easy to understand and work with? We do not yet have
enough experience to say for sure, but our experience to date suggests that the answer
is yes.
6.1 Modular, Concise and Explicit
Consider the following simple aspect, which is not part of the figure editor example.
This aspect implements a simple error logging functionality, in which every public
method defined on any type in the package logs any errors
it throws back to its caller.
Fig. 4. A portion of the screen when using the AspectJ-aware extension to emacs. The text i
[Square Brackets] following the method declarations is automatically generated, and serves to
remind the programmer of the aspects that crosscut the method.
aspect SimpleErrorLogging {
Log log = new Log();
pointcut publicEntries():
receptions(public **.*(..));
after() throwing (Error e): publicEntries() {
This aspect appears to be better than the plain Java implementation of the same
functionality in several ways:
The aspect is more modular. In the ordinary Java implementation, code for this
aspect would be spread across every public method.
The aspect is more concise. In the plain Java version something like six lines of
code would be added to each public method to wrap the body in a “try
catch…” statement.
The aspect is more explicit. In this code, the structural invariant underlying the
crosscutting is clear. A quick look at the code is all it takes to understand that all
the public methods defined in the package should do
error logging.
Consider a program maintenance scenario in which a programmer must work with
a system with this kind of functionality. In the plain Java implementation, the
programmer would discover the logging code one method at a time. After seeing
several such methods the programmer might guess that logging was being done by all
public methods of that class or perhaps even the package. But they would have to
make careful use of a tool like grep to be sure. And of course they might not even
make this guess.
In the AspectJ implementation, every public method would carry an annotation,
similar to that in Figures 3 and 4, so that when the programmer look at the first public
method they would see an annotation, something like that in Figures 3 and 4, which
would tell them that the method was crosscut by the
aspect. They could quickly go to the aspect, read the ten lines of code, and understand
the intent of the code. The structural invariant underlying the functionality – that all
public methods must log – would be clear and enforced.
Aspects that use explicit enumeration of method signatures can also be more
modular, concise and explicit than their plain Java counterparts. Consider the now
moves pointcut:
pointcut moves(FigureElement fe):
instanceof(fe) &&
(receptions(void FigureElement.incrXY(int, int)) ||
receptions(void Line.setP1(Point)) ||
receptions(void Line.setP2(Point)) ||
receptions(void Point.setX(int)) ||
receptions(void Point.setY(int)));
Even though this pointcut is enumeration rather than property-based, putting the
complete set of method signatures in a single place makes the crosscutting structure
explicit and clear. When reading the MoveTracking aspect it is easy to tell what
invariant it preserves – whenever something moves it records that fact. Writing the
Mobility aspect in terms of MoveTracking.moves, makes it clear that multiple
aspects of the implementation crosscut all the move operations. The IDE support
ensures that when we happen to be looking at the
setX method for Point, we see
Mobility and MoveTracking crosscut there. Navigating to either aspect will
show their structure and the fact that
Mobility is defined in terms of
This clarity is preserved when enumeration-based crosscutting is used together
with property-based crosscutting. This is evident in the
topLevelMoves pointcut.
pointcut topLevelMoves(FigureElement fe):
moves(fe) && !cflow(moves(FigureElement));
Our experience is that the cflow pointcut designator takes only a short while for
people learning AspectJ to learn, and once they do so, they find it quite easy to
understand this code. It is certainly much easier than to understand what is going on
from the middle of the classic tangled implementation of this functionality.
Clear explicit crosscutting structure can come from the way multiple advice
declarations interact as well. In the
SimpleTracing aspect of Section 3.8, there
are two advice declarations:
before(): tracePoints() {
printMessage(“Entering”, thisJoinPoint);
after(): tracePoints() {
printMessage(“Exiting”, thisJoinPoint);
Even without knowing what join points tracePoints will match, we
understand something important about the structure of this code – the entering and
exiting messages happen in pairs, on the way into and back out of join points matched
6.2 The Role of IDE Technology
IDE technology plays an important role in these scenarios. In the course of preparing
the paper we encountered a bug in which
MoveTracking and Mobility had
inconsistent moves pointcuts. The bug was immediately apparent, because the
environment showed numerous methods tagged with the
Mobility and
MoveTracking aspects and one method tagged with just MoveTracking.
Because it is now standard practice for OO programmers to use some kind of IDE
support and because it is so easy to incorporate AspectJ support into an IDE, we
believe it is reasonable to expect programmers to have IDE support available for such
The ability of the IDE to present the structure of the program depends on the
degree to which the code declaratively captures that structure. OO IDEs do a good job
of presenting inheritance structure because code in OO programming languages
captures inheritance explicitly. The AspectJ IDE support works well because code in
AspectJ captures crosscutting explicitly.
7 Related Work
In earlier work we proposed aspect-oriented programming [24] and presented three
examples of domain-specific [1] AOP languages [5] that we had developed. AspectJ
differs from those three systems in that it is a general-purpose language, it is
integrated with Java, it has a dynamic join point model, and we are developing a full
compiler, rather than just a pre-processor.
7.1 Other Work in AOP
Adaptive Programming [27] provides a special-purpose declarative language for
writing class structure traversal specifications. Using this language prevents
knowledge of the complete class structure from becoming tangled throughout the
code. Adaptive Components [36] build on adaptive programming by using similar
graph-language techniques to allow flexible linking of aspectual components and
classes. This makes aspectual components reusable. AspectJ supports reusable aspects
using the pointcut-overriding and advice-inheritance mechanism, neither of which
requires a special graph language.
Composition Filters [28] wrap objects inside of filters that operate on the messages
the objects receive. The filters have crosscutting access to the messages received by
an object. But attachment of filters to objects is done as part of class definitions, so
composition filters are less well suited than AspectJ for crosscuts that involve more
than one class.
De Volder has proposed a logic meta-programming (LMP) approach that can serve
as kind of an AOP language toolkit [32, 33]. In this approach, the equivalent of our
pointcut designators use logical queries to specify crosscuts. This approach can take
advantage of unification to define parametric pointcut designators. It supports higher-
order pointcut designators as well. We have considered extending AspectJ with this
kind of power, but have decided not to do so, in order to keep the language simpler
and easier for Java developers to learn quickly. We may re-consider this issue in
release 2.0 or later; we believe the current pointcut designator syntax leaves us room
to do so in an upward compatible way.
7.2 Multi-Dimensional Separation of Concerns
Subject-oriented programming is a means for composing and integrating disparate
class hierarchies (subjects), each of which might represent different concerns [9].
More recent work on multi-dimensional separation of concerns (MDSOC) [2, 19] is
intended to separate concerns along multiple dimensions at once. Hyper/J [15] is a
specific proposal for MDSOC. Hyper/J works by having the programmer write two
kinds of meta-declarations: The first describes how to slice concerns out of a set of
classes; the second describes how to re-compose those concerns into a new program.
Hyper/J has the potential to slice a concern out of code without re-factoring the
classes. By comparison, in AspectJ the separation of crosscutting concerns is done in
the original code, by writing it as an aspect. We believe re-factoring the code with an
aspect will be easier to maintain than slicing concerns out, but it is too soon to know.
7.3 Reflection
Computational reflection [19-22, 26, 38] enables crosscutting programs. For example,
it is possible to write a small piece of meta-code that runs for all methods. Smalltalk-
76 included meta-level functionality [12]. CommonLoops and 3-KRS proposed
different meta-level architectures for OO languages [3] PCL provided the first
efficient metaobject-protocol [25]. Much of the research in reflection has explored
varying the meta-level architecture to support different kinds of crosscutting [2] and
to achieve flexibility without sacrificing performance [34].
With the exception of reflective access to
thisJoinPoint, AspectJ has been
designed so that the semantics of advice is not a meta-programming nor a reflective
semantics. In particular, AspectJ the identifiers in pointcut designators do not refer to
program representation or interpreter state – they do not involve reification.
7.4 Object-Oriented Programming
Flavors [35], New Flavors [37], CommonLoops [16] and CLOS [34] all support
multiple-inheritance, declarative method combination and open classes. C++ supports
multiple inheritance [35]. While AspectJ includes elements of these, AspectJ also
provides more powerful and modular support for crosscutting than can be achieved
with these features.
Declarative method combination, as in the CLOS line of languages, is not
sufficient for AOP, because it lacks the pointcut mechanisms that enable crosscutting.
Ordinary multiple-inheritance (MI) is not sufficient for AOP for two reasons. First,
a single aspect can include advice for all the different participants in a multi-class
interaction. Using MI, a separate mixin-class must be defined for each participant
class. Second, aspects work by
reverse-inheritance – the aspect declares what classes
it should affect rather than vice-versa. This means that adding or removing aspects
from the system does not require editing affected class definitions.
Completely unstructured open classes, as in CLOS and its ancestors, enable some
degree of crosscutting modularity, but they do so in a totally unstructured way. In
AspectJ, classes and aspects are modular units, even if an aspect can crosscut classes.
Flavors, New Flavors and CLOS use the Common Lisp module system, called the package
system. It is typically used in only very coarse-grained ways, certainly not at the level of
single classes as in Java, and usually not even at the level of single packages in Java.
7.5 Other Work
Walker and Murphy have proposed a system based on implicit context that is also
intended to improve separation of concerns [37]. Implicit context is similar to AspectJ
in that the separation is made explicit in the source code. But it differs from AspectJ
in that it provides reflective access to the entire call history of a system. Thus explicit
context can reason about a wider dynamic context than is possible with
AspectJ programmers could write aspects to manually gather call history information
and thereby duplicate some explicit context functionality.
Implicit parameters provide dynamically scoped variables within a statically typed
Hinley Milner framework [16]. Implicit parameters are lexically distinct from regular
identifiers, and are bound by a special construct whose scope is dynamic, rather than
static as with let. Implicit parameters have some of the power of using cflow to pass
dynamic context. Implicit parameters are more powerful, in that the binding they
create can be set from any reference site. But they do not have explicit crosscutting
modularity support because references to the parameter are still spread throughout the
code. Many implementations of Scheme provide the fluid-let construct that
dynamically binds variables by side-effect, and then re-instates the previous binding
after evaluation of the body is completed.
8 Future Work
We plan to use AspectJ as the basis of an empirical assessment of aspect-oriented
programming. We want to develop a real AOP user community, and work with them
to understand the practical effects of AOP. Our main focus now is building up and
supporting the user community. To enable this, we are focusing on fine-tuning the
language design and improving the quality of the compiler, IDE extensions and
The compiler has three main limitations that we are currently working on: it uses
javac as a back-end rather than generating class files directly; it requires access to all
the source code for the system; and it performs a full recompilation whenever any part
of the user program changes. We believe we know how to build an incremental
compiler that will perform reasonably well on modestly large systems, but fast
incremental compilation for a language like AspectJ is definitely an area for future
In the tools area, we plan to support more IDEs. We will also make a crosscutting
structure browsing API that will allow others to develop tools that understand AspectJ
code. Our existing navigation model doesn’t capture the structure of
pointcuts as well as we would like, so this will also be an area for future work.
Beyond the 1.0 release we plan to explore new kinds of pointcut designators based
on dataflow properties of the program. Our goal with this functionality, which we call
dflow, is to be able to capture crosscuts such as the extent of a value and control
boundary crossings.
9 Summary
AspectJ is a seamless aspect-oriented extension to Java. Programming with AspectJ
feels like a small extension of programming with Java. AspectJ programs are largely
ordinary Java programs in which we use ordinary Java for class-like modularity, and
use aspects to implement crosscutting modularity.
Implementing crosscutting concerns using AspectJ benefits in three ways over a
plain Java implementation of the same functionality: the implementation is more
modular and concise; the structure of the crosscutting is captured in a more explicit
form; and because of the first two properties, programming environment tools can
help the programmer navigate and understand that structure.
Looking forward, our goal is to work with the AspectJ user community to assess
the benefits of using aspect-oriented programming, in more complex systems as well
as to continue to explore language design, methodological and other issues.
10 Acknowledgements
We thank the AspectJ users most of all. Their suggestions, questions and bug reports
have been invaluable in getting the project to where it is today. Without the users, this
project would not be possible.
Brian de Alwis, Yvonne Coady, Chris Dutchyn and Gail Murphy helped us with
detailed comments on the paper. Extensive comments from Bob Filman, Robert
Hirschfeld and the anonymous reviewers we also very helpful.
Our work builds on contributions from numerous past members of our research
group. In particular John Lamping and Cristina Lopes played major roles in getting
AOP and AspectJ to where they are today.
This work was partially supported by the Defense Advanced Research Projects
Agency under contract number F30602-C-0246. This work was also partially
supported by the Natural Sciences and Engineering Research Council (NSERC) of
Canada, Xerox Canada Limited and Sierra Systems. Java and Forte are trademarks of
Sun Microsystems. JBuilder is a trademark of Inprise Corporation.
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... Solidity is essentially an imperative language, and any AOP tool for the language will certainly borrow much from other tools for this class of languages, e.g. AspectC [3] and AspectJ [9]. Function entry and exit points are such joinpoints, which we adopt in AspectSol, allowing us to write aspects such as before call-to Wallet.addFunds() ...
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Aspect-oriented programming tools aim to provide increased code modularity by enabling programming of cross-cutting concerns separate from the main body of code. Since the inception of runtime verification , aspect-oriented programming has regularly been touted as a perfect accompanying tool, by allowing for non-invasive monitoring in-strumentation techniques. In this paper we present, AspectSol, which enables aspect-oriented programming for smart contracts written in Solidity , and then discuss the design space for pointcuts and aspects in this context. We present and evaluate practical runtime verification uses and applications of the tool.
... An example for such a framework is the OpenCOM [Cou+04] middleware. Dynamic aspect weaving is based on the principle of apsect-oriented programming and uses the ability of aspect languages such as AspectJ [Kic+01] to dynamically weave aspects at runtime, changing the behaviour of certain operations or creating new ones. ...
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Deep modelling has been in focus of research for more then two decades and found its way into state of the art modelling tools and frameworks. Hereby, many ideas refine and extend the initial concept of multilevel-metamodels. While all those works lay a solid foundation to the area of metamodelling and also attempt to utilise metamodelling environments at runtime, previous concepts focus on bottom-up methodology mainly, trying to find the most suitable metamodelling foundation or extending established formalisms to fulfil certain specific requirements. Previous works did not consider possible runtime interactions and explorations of highly variable deep-models by end-users throughoutly. We classify such user-driven systems based on deep-models at runtime to be a highly relevant future application scenario. With the techniques and concepts introduced in this work, we enable a top-down approach for userdriven system configuration of application-models at runtime. We follow a requirement based approach by analysing common scenarios in the context of business and workflow management to identify subsystems most suitable for remodelling by end-users. To showcase the idea of deep modelling in a real-world runtime context, we realise a concept based on the combination of traditional pattern-based design, deep-modelling and models at runtime. The results of this work are a ready-to-use microframework around the established composite structure of clabject hierarchies, for which we propose the Composite for Deep Instantiation (CoDI) design-pattern as a both high-level but implementation-optimised solution to match our vision of deep instantiation as a development oriented design choice, instead of just a powerful modelling concept.
This chapter studies software design and development considerations meant to improve maintainability of mobile apps. A maintainable mobile app is easy to understand and extend, adaptable to changes in its platform and environment, and portable across a multitude of smartphone platforms and environments. Section 4.1 starts this study by reviewing popular software patterns. A number of software patterns have been published over the years with the aim of improving abstraction , modularization, reusability , and/or modifiability . An app that has been designed according to well-known software patterns is likely to be more comprehensible and analyzable. Section 4.1 demonstrates adoption of some popular software patterns to facilitate examination of their other influences. Given that software analyzability is first and foremost for its maintenance, diagrams are often used as a valuable aid in improving clarity through picturization of software’s structure and behavior. Section 4.2 thus revisits UML (Unified Modeling Language ) and exemplifies the use of some standard UML diagrams in describing the design of mobile apps. Lastly, Section 4.3 highlights the portability challenges of mobile apps. Android and iOS currently dominate the mobile ecosystem. Developing an app only for Android means missing out on iOS market share. Managing multiple releases of an app on multiple hardware variants running different versions of Android OS or API levels is in itself a challenge, and the maintainability challenges are compounded if iOS is also included in the app’s roadmap. Using code examples from native, hybrid, and cross-platform mobile app development environments, Section 4.3 presents the choices currently available to support the portability of mobile apps.
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The Erlang programming language is used to build concurrent, distributed, scalable and resilient systems. Every component of these systems has to be thoroughly tested not only for correctness, but also for performance. Performance analysis tools in the Erlang ecosystem, however, do not provide a sufficient level of automation and insight needed to be integrated in modern tool chains. In this paper, we present : an extendable performance testing framework that combines the repeatability of load testing tools with the details on how the resources are internally used typical of the performance monitoring tools. These features allow to be integrated in the early stages of testing pipelines, providing users with a systematic approach to identifying performance issues. This paper introduces the framework, focusing on its features, design and imposed monitoring overhead measured through both theoretical estimates and trial runs on systems in production. The uniqueness of the features offered by , together with its usability and contained overhead prove that the framework can be a valuable resource in the development and maintenance of Erlang applications.
Serverless computing greatly simplifies the use of cloud resources. In particular, Function-as-a-Service (FaaS) platforms enable programmers to develop applications as individual functions that can run and scale independently. Unfortunately, applications that require fine-grained support for mutable state and synchronization, such as machine learning (ML) and scientific computing, are notoriously hard to build with this new paradigm. In this work, we aim at bridging this gap. We present Crucial , a system to program highly-parallel stateful serverless applications. Crucial retains the simplicity of serverless computing. It is built upon the key insight that FaaS resembles to concurrent programming at the scale of a datacenter. Accordingly, a distributed shared memory layer is the natural answer to the needs for fine-grained state management and synchronization. Crucial allows to port effortlessly a multi-threaded code base to serverless, where it can benefit from the scalability and pay-per-use model of FaaS platforms. We validate Crucial with the help of micro-benchmarks and by considering various stateful applications. Beyond classical parallel tasks (e.g., a Monte Carlo simulation), these applications include representative ML algorithms such as k -means and logistic regression. Our evaluation shows that Crucial obtains superior or comparable performance to Apache Spark at similar cost (18%–40% faster). We also use Crucial to port (part of) a state-of-the-art multi-threaded ML library to serverless. The ported application is up to 30% faster than with a dedicated high-end server. Finally, we attest that Crucial can rival in performance with a single-machine, multi-threaded implementation of a complex coordination problem. Overall, Crucial delivers all these benefits with less than 6% of changes in the code bases of the evaluated applications.
Enforcing authorization for web applications must be done on the server side. Thus, either the backend or the persistent storage are suitable layers. From a developer’s point of view, we want to use a framework to automate creating persistent storage models and to map the entities between storage and backend. However, not all such frameworks offer sufficient authorization support. From a scientist’s perspective, we want to generally combine the filtering capabilities of the persistent storage with the advantages of using a mapper framework. Therefore, we propose to intercept the communication between the backend and the mapper framework and thus provide a central point of authorization. This offers the advantage that developers are unlikely to inadvertently introduce security vulnerabilities. The request is modified by adding a filter to return only authorized entities. Filtering directly in the storage saves performance and bandwidth besides reducing development and maintenance effort.
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When solving a task, a programmer actively interacts with a finite set of code fragments. The information about their locations is important for quick navigation, for other developers, and as a kind of documentation. Integrated development environments (IDEs) provide tools for marking code fragments with labels, displaying lists of labels, and using these labels for quick navigation. However, they often lose the correspondence between the label and the marked place when the code is edited, in particular when changes are made outside the IDE. In previous works, the authors propose a tool to be integrated into various IDEs for “binding” to large syntactic entities of a program and building a markup that is robust to code editing. The description of the marked element is built on the basis of the abstract syntax tree (AST) of the program. Later it is used to algorithmically search for the element in an edited code. The search has a success rate from 99 to 100%. This article aims at robust algorithmic binding to an arbitrary section of the code. For binding to a single-line code fragment, we propose an extension of the model describing the marked fragment, and an additional search algorithm. We also propose an algorithm for embedding nodes corresponding to multi-line fragments in an AST. We show that the correctness of the AST is not violated by these embeddings. Bindings to randomly selected lines were made in the code of three large C# projects. Manual check of these lines search results in the edited code has confirmed that the bindings are robust to code editing.
При работе над задачей программист наиболее активно взаимодействует с конечным набором фрагментов кода. Информация об их расположении важна для быстрого перемещения между ними, для других разработчиков и как разновидность документации. Интегрированные среды разработки (IDE) позволяют связывать метки с участками кода, просматривать список меток и использовать их для быстрой навигации, однако связь между меткой и помеченным местом может теряться при редактировании кода, особенно при изменении за пределами IDE. В предыдущих работах авторами предлагается интегрируемый в IDE инструмент, позволяющий устойчиво к изменению кода помечать крупные синтаксические сущности программы («привязываться» к ним). Описание помечаемого элемента строится по абстрактному синтаксическому дереву (АСД) программы и используется для алгоритмического поиска этого элемента в отредактированном позднее коде. Поиск осуществляется с успешностью от 99 до 100%. Целью настоящей работы является устойчивая алгоритмическая привязка к произвольному участку кода. Для привязки к однострочному фрагменту кода предложены расширение модели, описывающей помечаемый фрагмент, и дополнительный алгоритм поиска. Введена необходимая формализация и предложен алгоритм встраивания в АСД узлов, соответствующих многострочным фрагментам; показано, что в результате такого встраивания не нарушается корректность АСД. В коде трёх крупных проектов на языке C# произведены привязки к случайно выбранным строкам. Ручной проверкой результатов поиска этих строк в отредактированном коде подтверждено, что привязка устойчива к редактированию кода.
This paper overviews some approaches to decentralized monitoring, where one considers systems with units of computation that are physically or logically distributed. Such systems are checked against specifications referring to the global behavior of the system. The problems that arise are (i) the absence of global observation point in the system, (ii) the partial view and evaluation of specifications on each component, and (iii) the need for communication. Decentralized monitoring addresses the placement of runtime monitors and their communication strategies, as well as the techniques, algorithms, and tools to make monitoring effective in such context.
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Behavioural Modelling – Foundations and Applications BM-FA2011 In collaboration with the Seventh European Conference on Modelling Foundations and Applications ECMFA 2011
This paper describes Symbolics’ newly redesigned object-oriented programming system, Flavors. Flavors encourages program modularity, eases the development of large, complex programs, and provides high efficiency at run time. Flavors is integrated into Lisp and the Symbolics program development environment. This paper describes the philosophy and some of the major characteristics of Symbolics’ Flavors and shows how the above goals are addressed. Full details of Flavors are left to the programmers’ manual, Reference Guide to Symbolics Common Lisp. (5).
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form only given on an article discussing Aspect-oriented programming.