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pattern |
Filterer |
filterer |
/patterns/filterer/ |
Design pattern that helps container-like objects to return filtered version of themselves.# short meta description that shows in Google search results |
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Filterer
The intent of this design pattern is to introduce a functional interface that will add a functionality for container-like objects to easily return filtered versions of themselves.
Real world example
We are designing a threat (malware) detection software which can analyze target systems for threats that are present in it. In the design we have to take into consideration that new Threat types can be added later. Additionally, there is a requirement that the threat detection system can filter the detected threats based on different criteria (the target system acts as container-like object for threats).
In plain words
Filterer pattern is a design pattern that helps container-like objects return filtered versions of themselves.
Programmatic Example
To model the threat detection example presented above we introduce Threat
and ThreatAwareSystem
interfaces.
public interface Threat {
String name();
int id();
ThreatType type();
}
public interface ThreatAwareSystem {
String systemId();
List<? extends Threat> threats();
Filterer<? extends ThreatAwareSystem, ? extends Threat> filtered();
}
Notice the filtered
method that returns instance of Filterer
interface which is defined as:
@FunctionalInterface
public interface Filterer<G, E> {
G by(Predicate<? super E> predicate);
}
It is used to fulfill the requirement for system to be able to filter itself based on threat
properties. The container-like object (ThreatAwareSystem
in our case) needs to have a method that
returns an instance of Filterer
. This helper interface gives ability to covariantly specify a
lower bound of contravariant Predicate
in the subinterfaces of interfaces representing the
container-like objects.
In our example we will be able to pass a predicate that takes ? extends Threat
object and
return ? extends ThreatAwareSystem
from Filtered::by
method. A simple implementation
of ThreatAwareSystem
:
public class SimpleThreatAwareSystem implements ThreatAwareSystem {
private final String systemId;
private final ImmutableList<Threat> issues;
public SimpleThreatAwareSystem(final String systemId, final List<Threat> issues) {
this.systemId = systemId;
this.issues = ImmutableList.copyOf(issues);
}
@Override
public String systemId() {
return systemId;
}
@Override
public List<? extends Threat> threats() {
return new ArrayList<>(issues);
}
@Override
public Filterer<? extends ThreatAwareSystem, ? extends Threat> filtered() {
return this::filteredGroup;
}
private ThreatAwareSystem filteredGroup(Predicate<? super Threat> predicate) {
return new SimpleThreatAwareSystem(this.systemId, filteredItems(predicate));
}
private List<Threat> filteredItems(Predicate<? super Threat> predicate) {
return this.issues.stream()
.filter(predicate)
.collect(Collectors.toList());
}
}
The filtered
method is overridden to filter the threats list by given predicate.
Now if we introduce a new subtype of Threat
interface that adds probability with which given
threat can appear:
public interface ProbableThreat extends Threat {
double probability();
}
We can also introduce a new interface that represents a system that is aware of threats with their probabilities:
public interface ProbabilisticThreatAwareSystem extends ThreatAwareSystem {
@Override
List<? extends ProbableThreat> threats();
@Override
Filterer<? extends ProbabilisticThreatAwareSystem, ? extends ProbableThreat> filtered();
}
Notice how we override the filtered
method in ProbabilisticThreatAwareSystem
and specify
different return covariant type by specifying different generic types. Our interfaces are clean and
not cluttered by default implementations. We we will be able to filter
ProbabilisticThreatAwareSystem
by ProbableThreat
properties:
public class SimpleProbabilisticThreatAwareSystem implements ProbabilisticThreatAwareSystem {
private final String systemId;
private final ImmutableList<ProbableThreat> threats;
public SimpleProbabilisticThreatAwareSystem(final String systemId, final List<ProbableThreat> threats) {
this.systemId = systemId;
this.threats = ImmutableList.copyOf(threats);
}
@Override
public String systemId() {
return systemId;
}
@Override
public List<? extends ProbableThreat> threats() {
return threats;
}
@Override
public Filterer<? extends ProbabilisticThreatAwareSystem, ? extends ProbableThreat> filtered() {
return this::filteredGroup;
}
private ProbabilisticThreatAwareSystem filteredGroup(final Predicate<? super ProbableThreat> predicate) {
return new SimpleProbabilisticThreatAwareSystem(this.systemId, filteredItems(predicate));
}
private List<ProbableThreat> filteredItems(final Predicate<? super ProbableThreat> predicate) {
return this.threats.stream()
.filter(predicate)
.collect(Collectors.toList());
}
}
Now if we want filter ThreatAwareSystem
by threat type we can do:
Threat rootkit = new SimpleThreat(ThreatType.ROOTKIT, 1, "Simple-Rootkit");
Threat trojan = new SimpleThreat(ThreatType.TROJAN, 2, "Simple-Trojan");
List<Threat> threats = List.of(rootkit, trojan);
ThreatAwareSystem threatAwareSystem = new SimpleThreatAwareSystem("System-1", threats);
ThreatAwareSystem rootkitThreatAwareSystem = threatAwareSystem.filtered()
.by(threat -> threat.type() == ThreatType.ROOTKIT);
Or if we want to filter ProbabilisticThreatAwareSystem
:
ProbableThreat malwareTroyan = new SimpleProbableThreat("Troyan-ArcBomb", 1, ThreatType.TROJAN, 0.99);
ProbableThreat rootkit = new SimpleProbableThreat("Rootkit-System", 2, ThreatType.ROOTKIT, 0.8);
List<ProbableThreat> probableThreats = List.of(malwareTroyan, rootkit);
ProbabilisticThreatAwareSystem simpleProbabilisticThreatAwareSystem =new SimpleProbabilisticThreatAwareSystem("System-1", probableThreats);
ProbabilisticThreatAwareSystem filtered = simpleProbabilisticThreatAwareSystem.filtered()
.by(probableThreat -> Double.compare(probableThreat.probability(), 0.99) == 0);
Pattern can be used when working with container-like objects that use subtyping, instead of parametrizing (generics) for extensible class structure. It enables you to easily extend filtering ability of container-like objects as business requirements change.
- Article about Filterer pattern posted on it's author's blog
- Application of Filterer pattern in domain of text analysis
One of the uses is present on the blog presented in
this link. It presents how
to use Filterer
pattern to create text issue analyzer with support for test cases used for unit
testing.
Pros:
- You can easily introduce new subtypes for container-like objects and subtypes for objects that are contained within them and still be able to filter easily be new properties of those new subtypes.
Cons:
- Covariant return types mixed with generics can be sometimes tricky
- Author of the pattern : Tomasz Linkowski