120,359 research outputs found
Transformation As Search
In model-driven engineering, model transformations are con- sidered a key element to generate and maintain consistency between re- lated models. Rule-based approaches have become a mature technology and are widely used in different application domains. However, in var- ious scenarios, these solutions still suffer from a number of limitations that stem from their injective and deterministic nature. This article pro- poses an original approach, based on non-deterministic constraint-based search engines, to define and execute bidirectional model transforma- tions and synchronizations from single specifications. Since these solely rely on basic existing modeling concepts, it does not require the intro- duction of a dedicated language. We first describe and formally define this model operation, called transformation as search, then describe a proof-of-concept implementation and discuss experiments on a reference use case in software engineering
Using ATL to define advanced and flexible constraint model transformations
Transforming constraint models is an important task in re- cent constraint
programming systems. User-understandable models are defined during the modeling
phase but rewriting or tuning them is manda- tory to get solving-efficient
models. We propose a new architecture al- lowing to define bridges between any
(modeling or solver) languages and to implement model optimizations. This
architecture follows a model- driven approach where the constraint modeling
process is seen as a set of model transformations. Among others, an interesting
feature is the def- inition of transformations as concept-oriented rules, i.e.
based on types of model elements where the types are organized into a hierarchy
called a metamodel
Event-Driven Network Model for Space Mission Optimization with High-Thrust and Low-Thrust Spacecraft
Numerous high-thrust and low-thrust space propulsion technologies have been
developed in the recent years with the goal of expanding space exploration
capabilities; however, designing and optimizing a multi-mission campaign with
both high-thrust and low-thrust propulsion options are challenging due to the
coupling between logistics mission design and trajectory evaluation.
Specifically, this computational burden arises because the deliverable mass
fraction (i.e., final-to-initial mass ratio) and time of flight for low-thrust
trajectories can can vary with the payload mass; thus, these trajectory metrics
cannot be evaluated separately from the campaign-level mission design. To
tackle this challenge, this paper develops a novel event-driven space logistics
network optimization approach using mixed-integer linear programming for space
campaign design. An example case of optimally designing a cislunar propellant
supply chain to support multiple lunar surface access missions is used to
demonstrate this new space logistics framework. The results are compared with
an existing stochastic combinatorial formulation developed for incorporating
low-thrust propulsion into space logistics design; our new approach provides
superior results in terms of cost as well as utilization of the vehicle fleet.
The event-driven space logistics network optimization method developed in this
paper can trade off cost, time, and technology in an automated manner to
optimally design space mission campaigns.Comment: 38 pages; 11 figures; Journal of Spacecraft and Rockets (Accepted);
previous version presented at the AAS/AIAA Astrodynamics Specialist
Conference, 201
Model-driven design, simulation and implementation of service compositions in COSMO
The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven support for service-oriented software development. In particular, it addresses how services and compositions of services can be designed, simulated and implemented. The support presented is part of a larger framework, called COSMO (COnceptual Service MOdelling). Whereas in previous work we reported on the conceptual support provided by COSMO, in this paper we proceed with a discussion of the practical support that has been developed. We show how reference models (model types) and guidelines (design steps) can be iteratively applied to design service compositions at a platform independent level and discuss what tool support is available for the design and analysis during this phase. Next, we present some techniques to transform a platform independent service composition model to an implementation in terms of BPEL and WSDL. We use the mediation scenario of the SWS challenge (concerning the establishment of a purchase order between two companies) to illustrate our application of the COSMO framework
Automated verification of model transformations based on visual contracts
The final publication is available at Springer via http://dx.doi.org/10.1007/s10515-012-0102-yModel-Driven Engineering promotes the use of models to conduct the different phases of the software development. In this way, models are transformed between different languages and notations until code is generated for the final application. Hence, the construction of correct Model-to-Model (M2M) transformations becomes a crucial aspect in this approach.
Even though many languages and tools have been proposed to build and execute M2M transformations, there is scarce support to specify correctness requirements for such transformations in an implementation-independent way, i.e., irrespective of the actual transformation language used.
In this paper we fill this gap by proposing a declarative language for the specification of visual contracts, enabling the verification of transformations defined with any transformation language. The verification is performed by compiling the contracts into QVT to detect disconformities of transformation results with respect to the contracts. As a proof of concept, we also report on a graphical modeling environment for the specification of contracts, and on its use for the verification of transformations in several case studies.This work has been funded by the Austrian Science Fund (FWF) under grant P21374-N13,
the Spanish Ministry of Science under grants TIN2008-02081 and TIN2011-24139, and the
R&D programme of the Madrid Region under project S2009/TIC-1650
Rewriting Constraint Models with Metamodels
An important challenge in constraint programming is to rewrite constraint
models into executable programs calculat- ing the solutions. This phase of
constraint processing may require translations between constraint programming
lan- guages, transformations of constraint representations, model
optimizations, and tuning of solving strategies. In this paper, we introduce a
pivot metamodel describing the common fea- tures of constraint models including
different kinds of con- straints, statements like conditionals and loops, and
other first-class elements like object classes and predicates. This metamodel
is general enough to cope with the constructions of many languages, from
object-oriented modeling languages to logic languages, but it is independent
from them. The rewriting operations manipulate metamodel instances apart from
languages. As a consequence, the rewriting operations apply whatever languages
are selected and they are able to manage model semantic information. A bridge
is created between the metamodel space and languages using parsing techniques.
Tools from the software engineering world can be useful to implement this
framework
Collaborative Verification-Driven Engineering of Hybrid Systems
Hybrid systems with both discrete and continuous dynamics are an important
model for real-world cyber-physical systems. The key challenge is to ensure
their correct functioning w.r.t. safety requirements. Promising techniques to
ensure safety seem to be model-driven engineering to develop hybrid systems in
a well-defined and traceable manner, and formal verification to prove their
correctness. Their combination forms the vision of verification-driven
engineering. Often, hybrid systems are rather complex in that they require
expertise from many domains (e.g., robotics, control systems, computer science,
software engineering, and mechanical engineering). Moreover, despite the
remarkable progress in automating formal verification of hybrid systems, the
construction of proofs of complex systems often requires nontrivial human
guidance, since hybrid systems verification tools solve undecidable problems.
It is, thus, not uncommon for development and verification teams to consist of
many players with diverse expertise. This paper introduces a
verification-driven engineering toolset that extends our previous work on
hybrid and arithmetic verification with tools for (i) graphical (UML) and
textual modeling of hybrid systems, (ii) exchanging and comparing models and
proofs, and (iii) managing verification tasks. This toolset makes it easier to
tackle large-scale verification tasks
Metamodel Instance Generation: A systematic literature review
Modelling and thus metamodelling have become increasingly important in
Software Engineering through the use of Model Driven Engineering. In this paper
we present a systematic literature review of instance generation techniques for
metamodels, i.e. the process of automatically generating models from a given
metamodel. We start by presenting a set of research questions that our review
is intended to answer. We then identify the main topics that are related to
metamodel instance generation techniques, and use these to initiate our
literature search. This search resulted in the identification of 34 key papers
in the area, and each of these is reviewed here and discussed in detail. The
outcome is that we are able to identify a knowledge gap in this field, and we
offer suggestions as to some potential directions for future research.Comment: 25 page
Automatically Discovering Hidden Transformation Chaining Constraints
Model transformations operate on models conforming to precisely defined
metamodels. Consequently, it often seems relatively easy to chain them: the
output of a transformation may be given as input to a second one if metamodels
match. However, this simple rule has some obvious limitations. For instance, a
transformation may only use a subset of a metamodel. Therefore, chaining
transformations appropriately requires more information. We present here an
approach that automatically discovers more detailed information about actual
chaining constraints by statically analyzing transformations. The objective is
to provide developers who decide to chain transformations with more data on
which to base their choices. This approach has been successfully applied to the
case of a library of endogenous transformations. They all have the same source
and target metamodel but have some hidden chaining constraints. In such a case,
the simple metamodel matching rule given above does not provide any useful
information
- …