SEKE 2012 Proceedings - Knowledge Systems Institute

Due to umlTUowl’s architecture the test cases are transparently
available and repeatable.
C. Time Complexity
Time complexity of the transformation implementation is
T = O(#N) ∗ [O(#G)+O(#Assoc)
(1)
+ O(#Attr)+O(#Com) ∗ O(#ComC)]
where #N is the number of XML elements (depending on
the XML serialization), #G is the number of class generalizations,
#Assoc the number of associations, #Attr the number
of attributes, #Com the number of comments and #ComC
the number of connections between classes/associations and
comments.
The comparison with Xu et al.’s solution[11] shows that
time complexity is slightly higher than O(#N). The main
reason is that the DOM structure of VP’s XMI 2.1 in some
cases has to be traversed, e.g. to map attributes and data
range, or to link comments to their corresponding entity. The
algorithm may be optimized (e.g. extracting data types into an
array before processing attributes), but the current algorithm
is broadly satisfactory.
D. Automated Testing
umlTUowl uses an elegant testing approach based on executable
test cases (jUnit): The tool is shipped with a variety
of test cases, which are linked with elaborate UML reference
models to cover common UML class diagram constructs as
defined in Table I. The unit tests are applied to particular elements
of the reference model’s diagrams, whereupon identical
diagrams have been created for each of the supported modeling
tools. For each converter implementation, an adequate XMI
file, images of the model’s diagrams created by the specific
modeling tool, and the related project files are provided. To
implement a new UML modeling editor’s XMI format, one just
has to extend an existing XMI converter, redraw the reference
model in the particular UML modeling tool and document
the export process of the newly implemented XMI version.
Due to leveraging, the intermediate meta model coding of test
cases is no longer necessary! Additional reference models can
be placed to support additional features for a specific UML
editor’s XMI file format. Adaption of not yet implemented
transformation features can be carried out across all existing
converters, hence the approach helps to gain high-quality
converters. Even UML-related models, such as MS Visio ERD,
can be implemented in adequate time.
E. Use Case: Transformation of Industrial Tank Model
Practitioners, especially designers and Quality Assurance
(QA) personnel, want to make complex industrial automation
systems more robust against normally hard to identify runtime
failures. Challenges to detect and locate defects at runtime
come from the different focus points of models. Without
an integrated view on relevant parts of both design-time
and runtime models inconsistencies from changes and their
impact are harder to evaluate and resolve. Better integrated
engineering knowledge can improve the quality of decisions
for runtime changes to the system, e.g., better handling severe
failures with predictable recovery procedures, lower level
of avoidable downtime, and better visibility of risks before
damage occurs [12][13][14]. As shown in [15], these problems
can be addressed with the help of ontologies and reasoning.
The CDL-Flex developed, domain-specific EKB provides
a better integrated view on relevant engineering knowledge
in typical design-time and runtime models, which were originally
not designed for machine-understandable integration.
It contains schemes on all levels and instances, data, and
allows reasoning to evaluate rules that involve information
from several models. umlTUowl in combination with the EKB
enables practitioners from different fields to create ontologies
out of previous or novel created UML (or similar) models on
the fly, and thus helps to gain better integrated and shared
knowledge across teams. It not only supports iterative development
of ontologies and hence helps to improve consistency
and compliance between design- and code/runtime- elements,
but also unburdens EKB ontology engineers so that they
can focus on modeling of complex logical relationships and
axioms.umlTUowl incorporates and centers domain experts
and helps improving the CDL-Flex EKB workflow transiently.
To demonstrate the integration of umlTUowl into
CDL-Flex’s EKB and to dig into a use case, the tool
has been validated against a previously-used, domain specific
tank model (compare [15]). Both, VP class data diagram
and OWL ontology that had been created in manual work
by CDL-Flex, have been provided beforehand. The UML
diagram models a piped tank that is connected to several
control elements, which ensure that the tank provides enough
fluid (eg. water or liquid chemical substances) and the content
is heated, dependent on the measures of different sensors.
The existing, manually created ontology and the umlTUowl
transformation result have been compared in Protégé and
were validated using ManchesterValidator. The results are
outlined next.
1) Class Transformation and Disjointness: The tool transformed
all 19 classes and considered all hierarchy levels
correctly. For instance, actuator is the superclass of heater,
pump and valves, while valve itself has been subdivided into
magnetic, manual and pneumatic classes. Unlike the manually
created ontology, disjointness of classes is not defined in
the umlTUowl created ontology. By default, UML classes
are defined as overlapping, so the ontology engineer has to
explicitly define disjoint classes, using Protégé.
2) Equivalent Classes: Of course the automated umlTUowl
transformation approach cannot distinguish equivalent and defined
classes. While the CDL-Flex ontology engineer defined
some equivalent classes in OWL, the tool created defined
classes with subclass axioms, instead.
3) Attributes: Because for none of the attributes a data type
had been specified in the UML diagram, the tool assigned data
range . The ontology engineer has to add missing
ranges to all data properties manually, e.g. set the data range
of (Domain = )to .
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