Unique identification of elements in evolving models [Elektronische Ressource] : towards fine-grained traceability in model-driven engineering / Sven Wenzel

Sven Wenzel

Informations

• Publié par: universitat_siegen
• Publié le: 01 janvier 2011
• Nombre de lectures: 16
• Langue: English
• Poids de l'ouvrage: 4 Mo

Extrait

Unique Identification of
Elements in Evolving Models:
Towards Fine-Grained Traceability in Model-Driven Engineering
Vom Fachbereich Elektrotechnik und Informatik der
Universitat¨ Siegen
zur Erlangung des akademischen Grades
Doktor der Naturwissenschaften
(Dr. rer. nat.)
genehmigte Dissertation
von
Dipl.-Inform. Sven Wenzel
Siegen, November 2010Gedruckt auf alterungsbestandigem¨ holz- und saur¨ efreiem Papier.
Als Dissertation genehmigt vom
Fachbereich Elektrotechnik und Informatik
Universitat¨ Siegen
Einreichung 3. November 2010
Mundl.¨ Prufung¨ 4. Marz¨ 2011
Dekan Prof. Dr. M. Pacas, Universitat¨ Siegen
1. Gutachter Prof. Dr. U. Kelter,at¨
2. Prof. T. Systa,¨ PhD, Techn. Universitat¨ Tampere, Finnland
3. Gutachter Prof. Dr. J. Ebert, Universitat¨ Koblenz
Vorsitzender Prof. Dr. V. Blanz,at¨ Siegeni
Abstract
Model-driven engineering (MDE) is a widely accepted methodology in software en-
gineering. At the same time, the ability to retrace the engineering process is an
important success factor for software projects. In MDE, however, such traceabil-
ity is often impeded by the inadequate management of model evolution. Although
models have a very fine-grained structure, their different revisions and variants
are prevalently managed as monoliths in a file-based software configuration man-
agement (SCM). This causes the identification problem: if the fine-grained ele-
ments are not assigned with globally unique identifiers, we cannot identify them
over time. If such identifiers would be given, they can be misleading. As a con-
sequence, we cannot comprehend the evolution of elements and traceability rela-
tionships among the elements cannot be managed sufficiently.
This thesis presents a novel solution to the identification problem. It establishes
a representation to describe the history of a model and its fine-grained elements
inside. The key feature of the representation is a new kind of traceability rela-
tionship, called identification links. They allow us to identify elements of a given
revision in other revisions or variants of the model. The identification is even ap-
plicable to anonymous elements and model fragments. It provides us with a broad
spectrum of opportunities: e.g. management of fine-grained traceability links, evo-
lution analysis, merging of development branches. Due to the expression of model
evolution in the history representation, we are further able to capture the changes
that have been applied to the traced elements. This thesis further presents an
algorithm to infer the identification links automatically. The approach does not
rely on persistent identifiers, but it utilizes a similarity-based model comparison
technique to locate the model elements in other revisions.
The algorithm and the history representation have been implemented in a proto-
type. It is metamodel and tool independent and can work with an arbitrary SCM.
Existing modeling environments do not have to be modified. Traceability informa-
tion and evolution information is accessible through a service interface and can
thus be integrated in arbitrary tools. The evaluation of our approach by means
of controlled experiments with data from real models attested excellent precision
and recall values for the identification of model elements over time. Furthermore,
different evolution analysis tools have already been built on our approach, which
documents the practical applicability of our solution.iiiii
Kurzfassung
Die modellgetriebene Entwicklung ist eine weit verbreitete Methode zur Softwa-
reentwicklung. Die ungeeignete Versionierung von Modellen verhindert jedoch oft-
mals die Nachverfolgbarkeit des Entwicklungsprozesses. Trotz ihrer feinkor¨ nigen
Struktur werden Modelle oft monolithisch auf Basis dateibasierter Konfigurations-
managementsysteme verwaltet. Modellelemente konnen¨ in diesem Fall nicht uber¨
die Zeit hinweg identifiziert werden, weil globale Identifizierer entweder fehlen oder
¨irrefuhr¨ end sein konnen.¨ Aufgrund dieses Identifikationsproblems konnen¨ An-
derungen an Modellelementen nur sehr schwer nachvollzogen werden. Außerdem
konnen¨ Referenzen zur Nachverfolgbarkeit zwischen Elementen verschiedener Re-
visionen nicht sinnvoll verwaltet werden.
Diese Dissertation lost¨ das Identifikationsproblem. Sie fuhrt¨ eine Reprasenta-¨
tion ein, mit der die Historie von Modellen und deren feinkor¨ nigen Elementen
abgebildet werden kann. Ein zentraler Bestandteil dieser Reprasentation¨ sind
Identifizierungslinks, die es ermoglichen¨ ein gegebenes Element in anderen Revi-
sionen oder Varianten des Modells wiederzufinden. Der Ansatz unterstutzt¨ auch
anonyme Elemente und komplette Modellfragmente. Diese neuartige Identifizie-
rung ermoglicht¨ z.B. die Verwaltung von feinkor¨ niger Nachverfolgbarkeitsinforma-
tion, die Analyse von Modellevolution oder das Mischen von Entwicklungszweigen.
Da die Reprasentation¨ auch die Evolution eines Modells abbilden kann, konnen¨
die Veranderungen¨ identifizierter Elemente besser erfasst werden. Zudem wird in
dieser Dissertation ein Algorithmus entwickelt, mit dem Identifizierungslinks zwi-
schen Modellelementen verschiedener Revisionen inferiert werden. Dieser stutzt¨
¨sich nicht auf persistente Identifizierer, sondern nutzt einen ahnlichkeitsbasierten
Differenzalgorithmus, um Elemente in anderen Revisionen wiederzufinden.
Der Algorithmus und die Historienreprasentation¨ wurden in einem modelltyp-
und werkzeugunabhangigen¨ Prototyp implementiert, der mit beliebigen Konfigura-
tionsmanagementsystemen zusammenarbeitet, ohne dass diese angepasst werden
mussen.¨ Die Informationen zur Nachverfolgbarkeit und Evolution von Modellele-
menten sind uber¨ eine Programmierschnittstelle abfragbar, die sich in beliebigen
Werkzeugen nutzen lasst.¨ Der beschriebene Ansatz wurde mit kontrollierten Ex-
perimenten auf Basis realer Modellhistorien erfolgreich evaluiert. Daruber¨ hinaus
wurde seine praktische Anwendbarkeit durch verschiedene darauf aufbauende
Werkzeuge zur Evolutionsanalyse belegt.ivv
Acknowledgements
I would like to thank my supervisor Professor Udo Kelter for his scientific support
and the endless discussions we had. I am also very grateful to my co-supervisors
Professor Tarja Systa¨ and Professor Jur¨ gen Ebert who encouraged and supported
me during the whole process of writing. They gave a lot of useful feedback and
inspiration that improved my thesis.
In addition, I would like to thank my (former) colleagues, Timo Kehrer, Maik
Schmidt, Pit Pietsch, Stefan Berlik, Christoph Treude, Jor¨ g Niere, Christian
Kohler¨ , Hamed Shariat Yazdi, Dhiah El Dhien Abou-Tair, and Maryam Nasiri, for
the discussions, for listening to my ideas, for co-authoring papers, and for proof
reading. Special thanks go to Roswitha Eifler and Frank Schuh for their orga-
nizational and technical support. They all provided me with a pleasant working
atmosphere including memorable coffee breaks with tons of cookies.
For the technical realization, I would like to thank all contributors of the SiDiff
project as well as the students Dennis Koch, Hermann Hutter, and Jens Falk
for their endurance while listening to my nebulous ideas and implementing them
in different prototypes. Furthermore, I would like to thank all students who have
supported me directly or indirectly with their diploma theses, their project groups,
or their work as student assistants.
I would further like to thank all of my friends and relatives for reminding me
of the other important things in life. I am especially grateful to my mother (who
died much too early), my father, and my brother for always supporting me and
inspiring me to bring out the best in myself.
Last but not least, I wish to express my deepest gratitute to my beloved wife for
her endless love, her patient care, and her unconditional support, and to my dear
children for filling me with joy and happiness. Thank you!vivii
There is no branch of detective science
which is so important and so much neglected
as the art of tracing footsteps.
— Sherlock Holmes
in “A Study in Scarlet” by Sir Arthur Conan Doyleviii