Systematic Mapping Study of Model Transformations for Concrete
Edouard Batot, Houari Sahraoui, Eugene Syriani, Paul Molins and Wael Sboui
DIRO, Universit
e de Montr
eal, Montr
eal, Canada
Model Transformation, Systematic Mapping, Software Engineering.
As a contribution to the adoption of the Model-Driven Engineering (MDE) paradigm, the research community
has proposed concrete model transformation solutions for the MDE infrastructure and for domain-specific
problems. However, as the adoption increases and with the advent of the new initiatives for the creation
of repositories, it is legitimate to question whether proposals for concrete transformation problems can be
still considered as research contributions or if they respond to a practical/technical work. In this paper, we
report on a systematic mapping study that aims at understanding the trends and characteristics of concrete
model transformations published in the past decade. Our study shows that the number of papers with, as main
contribution, a concrete transformation solution, is not as high as expected. This number increased to reach a
peak in 2010 and is decreasing since then. Our results also include a characterization and an analysis of the
published proposals following a rigorous classification scheme.
Model-Driven Engineering (MDE) has been gaining
much popularity in the last decade (Whittle et al.,
2014). It is an area of software engineering where
problems are expressed at levels of abstraction closer
to the problem domain, rather than the domain of
code, and software is realized through automated
transformation of domain models.
MDE, like any new technology, follows different
stages of adoption as described by (Moore, 2002). At
each stage, new contributions in research solve part of
the problems that represent major adoption obstacles.
One of the early obstacles to MDE adoption is the
difficulty to write and reuse model transformations
for many concrete problems. Indeed, the availabil-
ity of automated transformations is a prerequisite and
a founding principle of MDE.
In MDE, a model transformation is the automatic
manipulation of a model following a specification de-
fined at the level of metamodels (L
ucio et al., 2014).
It is an operation that accepts a source model as input
and produces a target model as output, where each
model conforms to its respective metamodel. Typ-
ically, a model transformation is defined by a set
of declarative rules to be executed (Czarnecki and
Helsen, 2006). As an example of transformation,
in (Syriani and Ergin, 2012), UML activity diagrams
are transformed into Petri nets for simulation and
analysis purposes.
With the concern of the adoption of the MDE
paradigm, the MDE research community has pro-
posed solutions to concrete model transformation
problems. These proposals can be classified into two
categories: transformations that improve the MDE in-
frastructure, such as code generators for programming
languages (Funk et al., 2008; Di Marco and Pace,
2013), and transformations for domain-specific prob-
lems (Winkler et al., 2012; Yue and Ali, 2012).
However, in recent years, two phenomena
changed the landscape of MDE. First, MDE is more
and more used in industry. Many studies showed
that this new technology is used on strategic projects
in many industrial organizations (Mohagheghi et al.,
2013).The second phenomenon is the advent of new
initiatives for the creation of publicly available repos-
itories of metamodels, models, and transformations
(e.g., ReMoDD (France et al., 2007) and ATL Trans-
formations Zoo
). In particular, the Transformation
Tool Contest (TTC)
proposes publicly available so-
lutions to specific problems expressed as model trans-
formations. Both phenomena change the needs in re-
search towards, among others, automated approaches
Batot, E., Sahraoui, H., Syriani, E., Molins, P. and Sboui, W.
Systematic Mapping Study of Model Transformations for Concrete Problems.
DOI: 10.5220/0005657301760183
In Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2016), pages 176-183
ISBN: 978-989-758-168-7
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
# exported records
# exported records
# records excluded
# manually added
# screened records
# papers assessed
for eligibility
# papers included in
the study
# excluded records
13 papers excluded
transformations not a
main contribution
Screening Eligibility Included
Figure 1: Flow of information during the selection process.
to derive MDE artifacts such as metamodel well-
formedness rules (Faunes et al., 2013) or model trans-
formations (Baki et al., 2014). In particular, it is legit-
imate to question whether proposals for specific arti-
facts, such as metamodels and transformations of con-
crete problems can still be considered as research con-
tributions, or if they respond to a practical need.
To help answering such a question, we conducted
a systematic mapping study (Petersen et al., 2008),
covering the last decade (2005-2014), that aims at un-
derstanding the trends and characteristics of model
transformations proposed for concrete problems and
published in research forums. We opted for a system-
atic empirical process to minimize bias and maximize
reproducibility of the study. In addition to study the
evolution of the amount of published material during
the considered period, we are also interested in var-
ious characteristics of these transformations such as
their nature, the used languages, the involved meta-
models, and the relation to industry.
Our results show that the number of papers with as
main contribution a concrete transformation increased
since 2005 to reach a peak in 2010, but has been de-
creasing since then. Among other results, the major-
ity of the proposals deals with general modeling lan-
guages as compared to proposals for domain-specific
problems. An interesting number of the proposals are
The remainder of the paper is organized as fol-
lows. In Section 2, we describe the paper selection
and analysis procedure. We report the results of the
systematic mapping using a predefined classification
scheme in Section 3. We briefly outline related work
in Section 4 and finally conclude in Section 5.
The following subsections describe the main activities
we performed (from (Petersen et al., 2008)) in order
to discover the trends in model transformation.
2.1 Research Objectives
As motivated in Section 1, the modeling community
values to know whether producing model transforma-
tions that solve concrete problems is useful and still
considered a research contribution. We, therefore,
formulate our research objectives with the following
two research questions:
RQ1: What are the trends in concrete model
RQ2: What are the characteristics of these trans-
2.2 Paper Selection
With these two objectives in mind, we determine the
scope of the search to be contributions in the litera-
ture, published between 2005 and 2014, that present
a model transformation for a concrete problem, e.g.,
transformation from UML activity diagrams to Petri
nets (Syriani and Ergin, 2012).
To retrieve the paper of interest, we queried the
Scopus database
. Moreover, we manually added pa-
pers to the corpus from the following specialized fo-
rums, which are likely to have papers of interest to
this study: ICMT, ECMFA, MODELS, and SOSYM.
As shown in Fig. 1, after the querying and filter-
ing, we obtained 544 papers from Scopus. For the
manual addition, we considered all the 591 long pa-
pers published in the four MDE forums between 2005
and 2014. After combining the two sources, a cor-
pus of 1 135 papers was considered for the screening
Screening is the most crucial phase in the system-
atic mapping process (Petersen et al., 2008). In order
to avoid the exclusion of papers that should be part of
the final corpus, we followed a strict screening proce-
dure. With four reviewers at our disposal (co-authors
of this paper), each article is screened by two review-
ers independently.
Scopus archives over 55 million records from over 5,000
Systematic Mapping Study of Model Transformations for Concrete Problems
Table 1: Classification scheme.
Category Description
Does the transformation operate on the
structure, mainly the syntax (e.g., migra-
tion), or on the behavior, mainly the se-
mantics (e.g., simulation), of the models
Do the input and output metamod-
els describe a general-purpose language
(e.g., UML, source code) or domain-
specific language?
Model kind
Do the transformed models come from in-
dustrial data (e.g., private), from publicly
available data (e.g., open-source), or from
made-up toy examples?
Under which intent category does the
transformation fall, as defined in (L
et al., 2014)?
Is the model transformation expressed us-
ing a dedicated language for transfor-
mations (e.g., ATL), a programming lan-
guage (e.g., Java), or in another way
(e.g., formally, without implementation)?
Is the transformation verified and vali-
dated formally (e.g., proving properties),
empirically (e.g., case study, validated on
multiple models), or is there no validation
(e.g., informal argumentation)?
Is the transformation exogenous (defined
on different metamodels), outplace (op-
erates on different models, but defined
on the same metamodel), or inplace (op-
erates on the same models) as defined
in (Mens and Van Gorp, 2006)?
Does the transformation involve an au-
thor from industry or only academic au-
thors are concerned?
A paper is included if its title or abstract explicitly
mentions a model transformation in its peculiar con-
text. It is excluded if either the transformation is not
the main topic of the paper or the abstract indicates
the paper proposes a generalization of a transforma-
tion technique rather than an actual concrete trans-
formation. Among the 1 135 screened papers, 1 040
were excluded, 83 were included directly (both re-
viewers agreed), and 12 were included after conflict
resolution, for a total of 95 papers. After screening,
the full text of the 95 papers were read in order to de-
tect situations where the abstract suggested to be in
favor of including the paper, whereas the content of
the paper suggested otherwise. This step excluded 13
additional papers from the study. Indeed, although
the reviewers concluded from the abstract that the pa-
pers satisfy the four criteria, the in-depth examination
showed that the proposed transformations did not rep-
resent the main contribution of the papers. The final
number of papers considered for the study is then 82
The complete list is available online geodes.
When we determined the objectives of this study,
we already had in mind some of the criteria with
which we were going to evaluate the papers. While
reading all the abstracts during screening, we re-
fined these criteria until we obtained the classifica-
tion scheme in Table 1. It will be used to classify all
retained papers along different categories that are of
interest in order to answer our research questions.
In this section, we analyze the retained papers accord-
ing to the classification scheme in order to answer the
research questions stated in Section 2.
8 8
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Specialized forums
General forums
Figure 2: Evolution of concrete model transformations.
3.1 Evolution of Concrete Model
The number of papers with a concrete model trans-
formation as a main concern increased since 2005 to
reach a peak in 2010 and has been decreasing since
then, as depicted in Fig. 2. We distinguish between
papers published in general software engineering fo-
rums and forums specialized in MDE. We note that
both general and specialized forums follow a similar
trend. However, we notice a shift towards specialized
forums around 2010. This is a recurring pattern that
often occurs when a new research community gains
popularity. The drop in 2013 may indicate that pro-
ducing concrete model transformations is becoming a
development task rather than a research endeavor.
3.2 Characteristics of Concrete Model
Now that we shed light on a general trend in the model
transformation community, we investigate the charac-
teristics of concrete model transformations in order
to answer RQ2, using the classification scheme pre-
sented in Table 1.
MODELSWARD 2016 - 4th International Conference on Model-Driven Engineering and Software Development
3.2.1 Intent
Figure 3: Distribution of intent category.
Three classes of intents account, each, for more than
10% of the classified papers, as depicted in Fig. 3.
The most popular transformation intent class is lan-
guage translation, which encompasses a third of the
analyzed transformations. Such transformations es-
tablish a bridge between a source and a target mod-
eling language to achieve tasks that are difficult (or
impossible) to perform on the source language (Yang
et al., 2014) or to make use of a specific tool (Winkler
et al., 2012). The second most frequent class of intent
is refinement with 22%. Code synthesis is the domi-
nant transformation as in (Di Marco and Pace, 2013),
where wireless sensor network code is generated from
a UML profile. Nevertheless, other kinds of refine-
ments are also present, such as refining a require-
ment model into a platform-independent model of a
multi-agent system (Harbouche et al., 2013). Seman-
tic definition is another predominant intent class with
12%. On the one hand, there are simulation trans-
formations that encode the operational semantics of a
language. On the other hand, there are translational
semantics transformations, whose purpose is to trans-
late one metamodel into another in order to define its
semantics, as in (Wagelaar et al., 2012). The lesser
popularity of the remaining intents (10% or less) is
due to the fact that approaches to perform, for exam-
ple, analysis and visualization, already exist in non-
MDE technologies. Therefore, the community has
not been focusing on explicitly modeling these tasks
by means of model transformation.
3.2.2 Transformation Kind
As depicted in Fig. 4 (right), a striking majority of the
papers deal with structural transformations. Behav-
ioral transformations are scarce, mostly designed to
analyze software evolution and perform simulations.
This accords with the distribution of intents. (G
et al., 2005) were precursors and showed how “one
can manipulate time information just like structural
information”. In fact, analysis or simulation of the
behavior of systems through transformations are of-
ten preceded by a structural translation of models,
in order to reuse existing tools: e.g., transforming a
domain-specific language or UML (Anastasakis et al.,
2007) into Alloy for analysis purposes.
3.2.3 Scope
Figure 4: Distribution of scope and transformation kind cat-
The lack of experience of the community in terms
of endogenous transformation is put to light in Fig. 4
(left). Only 13% of the transformations were en-
dogenous, inplace (e.g., simulating the token behav-
ior of Petri nets (Syriani and Ergin, 2012)) or out-
place (e.g., performing row and column manipula-
tions on spreadsheets (Cunha et al., 2012)). In fact,
this corroborates with the intent distribution, since the
three most popular intents are typically implemented
by means of exogenous transformations. Many of
the proposed endogenous transformations are imple-
mented by mean of graph transformations (see, for
example, (Amelunxen and Sch
urr, 2008)). In addition
to refactoring, simulation and analysis, metamodel-
model co-evolution and metamodel-transformation
co-evolution (e.g., (Garc
es et al., 2014)) are naturally
favored application domains, as they require modify-
ing existing models. Other papers deal with model
synchronization (under the model composition intent
class), which is a special case as one can see it as an
exogenous transformation. Indeed, the synchroniza-
tion is performed between two models, generally be-
longing to two different metamodels. However, syn-
chronization can also be seen as the evolution of a
given model to handle new constraints resulting from
the modification of another model. This is the case,
for example, in (Xiong et al., 2013) where the au-
thors propose an algorithm for synchronizing concur-
rent models.
Systematic Mapping Study of Model Transformations for Concrete Problems
3.2.4 Metamodel Kind
Figure 5: Distribution of metamodel-kind and
tansformation-language category.
Fig. 5 (left) shows the distribution of combina-
tions between general-purpose and domain-specific
source and target metamodels of a transforma-
tion. Overall, two thirds of the approaches fa-
vor reusing existing tooling to simulate their sys-
tems, thus transforming between general-purpose lan-
guages (e.g., (Denil et al., 2014)). In particular, (a
subset of) UML is the most frequently used meta-
model. General-purpose languages, such as Ecore
(UML), XML (Eichberg et al., 2010), and Petri
nets (Syriani and Ergin, 2012), are mostly used as
target, again to favor reuse of existing technologies.
Domain-specific metamodels are typically used in
transformations to translate from one language to an-
other (Acher et al., 2009). Most of the papers involv-
ing source and/or target domain-specific metamodels
deal with business concerns, like business models in
(Siqueira and Silva, 2014). Other domain-specific to
general-purpose language transformations range from
particular aspects of application development such as
user-interface generation (Pastor, 2007) to very spe-
cific domains like configuration of video surveillance
systems (Acher et al., 2009). Finally, a representa-
tive case of DSL-to-DSL transformations is the one
in (Selim et al., 2012). In this work, the transforma-
tion aims at migrating models expressed using a Gen-
eral Motors domain-specific language to AUTOSAR.
3.2.5 Transformation Language
As Fig. 5 (right) illustrates, more than half of the
transformations are implemented in a language dedi-
cated to model transformations. Half of those are im-
plemented in languages considered de facto standards
(ATL (Wagelaar et al., 2012) and QVT (Siqueira
and Silva, 2014)), and the other half with less pop-
ular languages (Pastor, 2007).Only 18% of the papers
still used programming languages for their transfor-
mations. These are mainly written in Java for the
Eclipse platform (Buchmann et al., 2011), but also
Prolog (Eichberg et al., 2010) and XSLT. The remain-
ing 29% of the papers only described the transfor-
mation, either without implementation or by imple-
menting it in a one-time use tool (Yue and Ali, 2012).
These observations reveal that model transformation
is being recognized as a paradigm in itself.
3.2.6 Model Kind and Orientation
On the one hand, in the vast majority of cases, we
found that scalable examples are not a priority: over
two-thirds of the papers illustrate their results with
toy examples, often made up for the particular work.
Although these toy examples cannot provide com-
pelling evidence about the quality of the proposed
transformation, they have the advantage of clearly il-
lustrate the transformation and then favor its adop-
tion by the potential users (Whittle et al., 2014). On
the other hand, industrial data shows how strong-built
and scalable the technology is. Among the few cases
where large sets of industrial data are involved, it
is worth mentioning the work by (Hermann et al.,
2014), in which data provided by satellite Astra is
used to validate the proposed transformation. Some-
times, although industrial data is used, its size is too
small to produce compelling evidence of the qual-
ity/usefulness of the proposed transformation (Selim
et al., 2012). Larger data models, from industry or
that are publicly available, have been slowly gain-
ing momentum in the past few years (Yue and Ali,
2012), as indicated in Fig. 6. This is certainly influ-
enced by the fact that an industrial stakeholder was
involved for 20% of the papers, which has happened
predominantly in the 2010-2012 period. It is interest-
ing to note that papers with industrial authors follow
the same trend as those with academic authors only:
most publications in 2010, mainly exogenous trans-
formations, but with more industrial models.
3.2.7 Validation
Concrete model transformations are being validated
empirically more often with time (see Fig. 6). This
observation corroborates with a previous study in
2011 (Carver et al., 2011). Indeed, since 2011, MOD-
ELS has increased the number of pages for submis-
sions in order to give more space for a discussion
about validation. Half of the papers have validated
their work empirically as in (Yue and Ali, 2012), with
a peak in 2012. Nevertheless, most validations were
performed on small examples (Siqueira and Silva,
2014) which reduces the scalability of the validation
MODELSWARD 2016 - 4th International Conference on Model-Driven Engineering and Software Development
Model kind
No Validation
Figure 6: Evolution of validation, model kind and orientation, and their influences.
to its peculiar context. Furthermore, Fig. 6 shows
that a drop in studies using toy models correlates
with the increase of empirical validation. With re-
spect to the forms of validation, case studies are the
most used with, as mentioned earlier, small illustrat-
ing examples. Still, some contributions, such as (Her-
mann et al., 2014) and (Yue and Ali, 2012), pro-
pose strongly built validations, addressing both per-
formances and accuracy aspects. Validation is also
made by simulation as in (Denil et al., 2014) but they
remain scarce. Finally, in the very few papers that use
theoretical validation, this is implicit as the proposed
transformation is itself described formally.
3.3 Discussion
With respect to RQ1, after tracing correspondences
between the statistical results from this classification,
there are two possible explanations for the trend ob-
served in Fig. 2: either the interest in model trans-
formation is decreasing or the model transformation
community has reached an appropriate level of ma-
turity and adoption since 2013. However, the for-
mer should be discarded because of the continued
popularity of transformation-exclusive venues: ICMT
and TTC. Indeed, its main artifacts—concrete model
transformations—have been pulling out from the re-
search literature since 2009 and are becoming con-
sidered as development tasks. This observation is
corroborated by the recent survey in (Whittle et al.,
2014), in which, a large number of surveyed actors
use MDE with concrete domain-specific artifacts. By
no means should one conclude that all transformation
problems have been solved. Instead, this indicates
that significant scientific contributions are now being
exploited to solve practical problems.
Answering RQ2 suggests that the model transfor-
mation community has favored exploring exogenous
transformations, that are structural in order to trans-
late, refine/synthesize code, or to give precise mean-
ing to models. This is mainly a consequence of want-
ing to reuse existing non-modeled software, as op-
posed to modeling the solution in a model transfor-
mation for behavioral transformations, such as anal-
ysis and simulation. As a result, a plethora of tools
have emerged for implementing model transforma-
tion, without one clear outlier. Although languages
dedicated to model transformations are preponderant,
programming languages are still used. From another
perspective, transformations are seizing to be applied
on toy models and, since 2010, are becoming more
applied in larger case studies. Finally, research in
model transformations is heading for a more stable
and grounded validation. The number of studies val-
idated empirically has been gradually increasing in
the past decade. This confirms the level of maturity
reached by model transformation, as stated for RQ1.
Several works attempted to classify model transfor-
mations. However, to the best of our knowledge, this
paper is the first to propose a systematic mapping
study for model transformations.
(Mens and Van Gorp, 2006) proposed a taxonomy
of model transformation based on how models are
manipulated and their execution strategies. Related to
this contribution, (Czarnecki and Helsen, 2006) clas-
sified the features offered by languages to express
model transformations. For a separate but related
matter, (L
ucio et al., 2014) have cataloged the differ-
ent use cases and intents where a model transforma-
tion can be used.
Nevertheless, there have been several empirical
studies about various aspects of MDE. Concerning
the MDE adoption, (Hutchinson et al., 2011; Mo-
hagheghi et al., 2013) performed user studies in the
form of interviews and surveys among developers to
investigate how MDE technologies are applied in in-
dustry. Similarly and with respect to the development
Systematic Mapping Study of Model Transformations for Concrete Problems
process, (Mart
ınez et al., 2014) compared the perfor-
mance of maintenance tasks when using an MDE ap-
proach against a code-centric approach.
From a product perspective, (Vanderose and
Habra, 2008) propose an approach to empirically
evaluate quality factors of developed artifacts in
MDE. In the same vein, (Fernandez et al., 2013) per-
formed a series of user studies to assess the usability
of web applications developed in an MDE process.
The closest study to the one in this paper
is (Carver et al., 2011): a systematic survey focused
on MODELS in order to understand the frequency with
which empirical evaluations have been reported.
In this paper, we report on a systematic mapping study
to understand the trends and characteristics of model
transformations for concrete problems. Our study
uses a major online database, Scopus, along with the
published articles in the four major MDE forums.
This study, which covers the period 2005-2014, was
conducted following the systematic mapping process.
First, we collected all publications found by query-
ing the database and by gathering the papers of the
specialized forums. Then, we screened them using
their abstract to ensure that they were eligible for our
analysis. Finally, we analyzed every included article
to classify the proposed transformation according to a
predefined scheme.
In addition to the findings discussed throughout
this paper, our study is a contribution to a global
assessment of the state of research and adoption of
MDE. Indeed, as for any new technology, it is our
duty as a research community to reflect globally on
what is relevant for research and what should be
treated as technical problems. In this context, we plan
to periodically repeat this study to have an up-to-date
portray of the situation. We also plan to perform a
similar study on additional MDE artifacts, in partic-
ular, metamodels. Finally, the classification scheme
will be evolved to take into consideration new re-
search results.
Acher, M., Lahire, P., Moisan, S., and Rigault, J.-P. (2009).
Tackling high variability in video surveillance systems
through a model transformation approach. In Models
in Soft. Eng.
Amelunxen, C. and Sch
urr, A. (2008). Formalising model
transformation rules for UML/MOF 2. IET Software,
Anastasakis, K., Bordbar, B., Georg, G., and Ray, I. (2007).
UML2Alloy: A Challenging Model Transformation.
In Proc. of the Int. Conf. on Model-Driven Engineer-
ing Languages and Systems.
Baki, I., Sahraoui, H., Cobbaert, Q., Masson, P., and
Faunes, M. (2014). Learning Implicit and Explicit
Control in Model Transformations by Example. In
Proc. of the Int. Conf. on Model-Driven Engineering
Languages and Systems.
Buchmann, T., Westfechtel, B., and Winetzhammer, S.
(2011). ModGraph-A Transformation Engine for
EMF Model Transformations. In Int. Conf. on Soft-
ware and Data Technologies.
Carver, J. C., Syriani, E., and Gray, J. (2011). Assessing the
Frequency of Empirical Evaluation in Software Mod-
eling Research. In EESSMod, volume 785.
Cunha, J., Fernandes, J. P., Mendes, J., Pacheco, H., and
Saraiva, J. (2012). Bidirectional Transformation of
Model-Driven Spreadsheets. In Theory and Practice
of Model Transformations.
Czarnecki, K. and Helsen, S. (2006). Feature-Based Survey
of Model Transformation Approaches. IBM Systems
J., 45(3).
Denil, J., Mosterman, P. J., and Vangheluwe, H. (2014).
Rule-based model transformation for, and in simulink.
In Symposium on Theory of Modeling and Simulation.
Di Marco, A. and Pace, S. (2013). Model-driven approach
to Agilla Agent generation. In Wireless Communica-
tions and Mobile Computing Conf.
Eichberg, M., Monperrus, M., Kloppenburg, S., and
Mezini, M. (2010). Model-Driven Engineering of Ma-
chine Executable Code. In Proc. of the Eur. Conf. on
Modelling Foundations and Applications.
Faunes, M., Cadavid, J., Baudry, B., Sahraoui, H., and
Combemale, B. (2013). Automatically Searching for
Metamodel Well-Formedness Rules in Examples and
Counter-Examples. In Proc. of the Int. Conf. on
Model-Driven Engineering Languages and Systems.
Fernandez, A., Abrah
ao, S., and Insfran, E. (2013). Em-
pirical validation of a usability inspection method for
model-driven Web devt. Int. J. on Soft. and Systems
Modeling, 86.
France, R., Bieman, J., and Cheng, B. (2007). Repository
for Model Driven Devt (ReMoDD). In Models in Soft-
ware Engineering, volume 4364.
Funk, M., Nyßen, A., and Lichter, H. (2008). From UML to
ANSI-C - An Eclipse-Based Code Generation Frame-
work. In Int. Conf. on Software and Data Technolo-
es, K., Vara, J. M., Jouault, F., and Marcos, E. (2014).
Adapting transformations to metamodel changes via
external transformation composition. Int. J. on Soft.
and Systems Modeling.
ırba, T., Favre, J.-M., and Ducasse, S. (2005). Using
Meta-Model Transformation to Model Software Evo-
lution. Electronic Notes in Theoretical Computer Sci-
ence, 137(3).
Harbouche, A., Erradi, M., and Mokhtari, A. (2013). Deriv-
ing Multi-Agent System Behavior. Int. J. of Soft. Eng.
and Its Applications, 7(4).
MODELSWARD 2016 - 4th International Conference on Model-Driven Engineering and Software Development
Hermann, F., Gottmann, S., Nachtigall, N., Ehrig, H.,
Braatz, B., Morelli, G., Pierre, A., Engel, T., and Er-
mel, C. (2014). Triple Graph Grammars in the Large
for Translating Satellite Procedures. In Int. Conf. on
Theory and Practice of Model Transformations.
Hutchinson, J., Whittle, J., Rouncefield, M., and Kristof-
fersen, S. (2011). Empirical assessment of MDE in
industry. In Proc. of the Int. Conf. on Software Engi-
ucio, L., Amrani, M., Dingel, J., Lambers, L., Salay,
R., Selim, G., Syriani, E., and Wimmer, M. (2014).
Model transformation intents and their properties. Int.
J. on Soft. and Systems Modeling.
ınez, Y., Cachero, C., and Meli
a, S. (2014). Empiri-
cal study on the maintainability of Web applications:
Model-driven Engineering vs Code-centric. Empirical
Soft. Eng., 19(6).
Mens, T. and Van Gorp, P. (2006). A Taxonomy of Model
Transformation. In Int. Work. on Graph and Model
Transformation, volume 152.
Mohagheghi, P., Gilani, W., Stefanescu, A., and Fernandez,
M. (2013). An empirical study of the state of the prac-
tice and acceptance of mde in four industrial cases.
Empirical Soft. Eng.
Moore, G. (2002). Crossing the Chasm: Marketing
and Selling Disruptive Products to Mainstream Cus-
O. (2007). Generating User Interfaces from Con-
ceptual Models: A Model-Transformation Based Ap-
proach. In Computer-Aided Design of User Interfaces
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M.
(2008). Systematic Mapping Studies in Software En-
gineering. In Int. Conf. on Evaluation and Assessment
in Soft. Eng., EASE’08.
Selim, G. M. K., Wang, S., C., J. R., and Dingel, J. (2012).
Model Transformations for Migrating Legacy Models:
An Industrial Case Study. In Proc. of the Eur. Conf.
on Modelling Foundations and Applications.
Siqueira, F. L. and Silva, P. S. M. (2014). Transforming
an enterprise model into a use case model in business
process systems. Int. J. on Soft. and Systems Model-
ing, 96.
Syriani, E. and Ergin, H. (2012). Operational Semantics
of UML Activity Diagram: An Application in Project
Management. In RE 2012 Workshops.
Vanderose, B. and Habra, N. (2008). Towards a generic
framework for empirical studies of Model-Driven En-
gineering. In Work. on Empirical Studies of MDE.
Wagelaar, D., Iovino, L., Di Ruscio, D., and Pierantonio,
A. (2012). Translational Semantics of a Co-evolution
Specific Language with the EMF Transformation Vir-
tual Machine. In Theory and Practice of Model Trans-
Whittle, J., Hutchinson, J., and Rouncefield, M. (2014). The
state of practice in model-driven engineering. Soft-
ware, IEEE, 31.
Winkler, U., Fritzsche, M., Gilani, W., and Marshall, A.
(2012). BOB the Builder: A Fast and Friendly Model-
to-PetriNet Transformer. In Proc. of the Eur. Conf. on
Modelling Foundations and Applications.
Xiong, Y., Song, H., Hu, Z., and Takeichi, M. (2013). Syn-
chronizing concurrent model updates based on bidi-
rectional transformation. Int. J. on Soft. and Systems
Modeling, 12(1).
Yang, Z., Hu, K., Ma, D., Bodeveix, J.-P., Pi, L., and Talpin,
J.-P. (2014). From {AADL} to Timed Abstract State
Machines: A verified model transformation. Int. J. on
Soft. and Systems Modeling, 93.
Yue, T. and Ali, S. (2012). Bridging the Gap between
Requirements and Aspect State Machines to Support
Non-functional Testing: Industrial Case Studies. In
Proc. of the Eur. Conf. on Modelling Foundations and
Applications, volume 7349.
Systematic Mapping Study of Model Transformations for Concrete Problems