Quoting directly from the paper:
To illustrate the precise problems of the observer pattern,
we start with a simple and ubiquitous example: mouse dragging.
The following example traces the movements of the
mouse during a drag operation in a Path object and displays
it on the screen. To keep things simple, we use Scala closures
as observers.
var path: Path = null
val moveObserver = { (event: MouseEvent) =>
path.lineTo(event.position)
draw(path)
}
control.addMouseDownObserver { event =>
path = new Path(event.position)
control.addMouseMoveObserver(moveObserver)
}
control.addMouseUpObserver { event =>
control.removeMouseMoveObserver(moveObserver)
path.close()
draw(path)
}
The above example, and as we will argue the observer
pattern as defined in [25] in general, violates an impressive
line-up of important software engineering principles:
Side-effects Observers promote side-effects. Since observers
are stateless, we often need several of them to simulate
a state machine as in the drag example. We have to save
the state where it is accessible to all involved observers
such as in the variable path above.
Encapsulation As the state variable path escapes the scope
of the observers, the observer pattern breaks encapsulation.
Composability Multiple observers form a loose collection
of objects that deal with a single concern (or multiple,
see next point). Since multiple observers are installed at
different points at different times, we can’t, for instance,
easily dispose them altogether.
Separation of concerns The above observers not only trace
the mouse path but also call a drawing command, or
more generally, include two different concerns in the
same code location. It is often preferable to separate the
concerns of constructing the path and displaying it, e.g.,
as in the model-view-controller (MVC) [30] pattern.
Scalablity We could achieve a separation of concerns in our
example by creating a class for paths that itself publishes
events when the path changes. Unfortunately, there is no
guarantee for data consistency in the observer pattern.
Let us suppose we would create another event publishing
object that depends on changes in our original path, e.g.,
a rectangle that represents the bounds of our path. Also
consider an observer listening to changes in both the
path and its bounds in order to draw a framed path. This
observer would manually need to determine whether the
bounds are already updated and, if not, defer the drawing
operation. Otherwise the user could observe a frame on
the screen that has the wrong size (a glitch).
Uniformity Different methods to install different observers
decrease code uniformity.
Abstraction There is a low level of abstraction in the example.
It relies on a heavyweight interface of a control
class that provides more than just specific methods to install
mouse event observers. Therefore, we cannot abstract
over the precise event sources. For instance, we
could let the user abort a drag operation by hitting the escape
key or use a different pointer device such as a touch
screen or graphics tablet.
Resource management An observer’s life-time needs to be
managed by clients. Because of performance reasons,
we want to observe mouse move events only during a
drag operation. Therefore, we need to explicitly install
and uninstall the mouse move observer and we need to
remember the point of installation (control above).
Semantic distance Ultimately, the example is hard to understand
because the control flow is inverted which results
in too much boilerplate code that increases the semantic
distance between the programmers intention and
the actual code.
[25] E. Gamma, R. Helm, R. Johnson, and J. Vlissides. Design
patterns: elements of reusable object-oriented software.
Addison-Wesley Longman Publishing Co., Inc., Boston, MA,
USA, 1995. ISBN 0-201-63361-2.