Model Transformation Language Research Articles

Using internal domain-specific languages to inherit tool support and modularity for model transformations

Model-driven engineering (MDE) has proved to be a useful approach to cope with today’s ever-growing complexity in the development of software systems; nevertheless, it is not widely applied in industry. As suggested by multiple studies, tool support is a major factor for this lack of adoption. In particular, the development of model transformations lacks good tool support. Additionally, modularization techniques are inevitable for the development of larger model transformations to keep them maintainable. Existing tools for MDE, in particular model transformation approaches, are often developed by small teams and cannot keep up with advanced tool support for mainstream general-purpose programming languages, such as IntelliJ or Visual Studio. Internal DSLs are a promising solution to these problems. In this paper, we investigate the impact of design decisions of an internal DSL to the reuse of tool support and modularization concepts from the host language. We validate our findings in terms of understandability, applicability, tool support, and extensibility using three case studies from academia, a model-driven engineering platform, and the industrial automation domain where we apply an implementation of an internal model transformation language on the .NET platform. The results confirm the value of inherited modularity and tool support while conciseness and understandability are still competitive.

Model transformation between OPC UA and UML

OPC Unified Architecture (UA) is a platform-independent standard for message-based communication between clients and servers on various types of network to facilitate information exchange. OPC UA has been adopted in various domains such as power grids, building automation, and smart devices to support interoperability of involved systems. These domains also use Unified Modeling Language (UML) as the standard notation for data modeling or system modeling. Use of two different notations in the same domain causes compatibility issues. To address this, we present an approach for transforming OPC UA to UML to improve their compatibility and integration. In the approach, we rigorously analyze the semantics of OPC UA elements and establish a mapping between OPC UA elements and UML elements based on the analysis. Based on the mapping, we define transformation algorithms using Query/View/Transformation (QVT) which is a standard model transformation language by OMG. We demonstrate the approach using case examples in the power grid, building automation, and smart device domains.

Automating feature model refactoring: A Model transformation approach

Context: Feature model is an appropriate and indispensable tool for modeling similarities and differences among products of the Software Product Line (SPL). It not only exposes the validity of the products’ configurations in an SPL but also changes in the course of time to support new requirements of the SPL. Modifications made on the feature model in the course of time raise a number of issues. Useless enlargements of the feature model, the existence of dead features, and violated constraints in the feature model are some of the key problems that make its maintenance difficult.Objective: The initial approach to dealing with the above-mentioned problems and improving maintainability of the feature model is refactoring. Refactoring modifies software artifacts in a way that their externally visible behavior does not change.Method: We introduce a method for defining refactoring rules and executing them on the feature model. We use the ATL model transformation language to define the refactoring rules. Moreover, we provide an Alloy model to check the feature model and the safety of the refactorings that are performed on it.Results: In this research, we propose a safe framework for refactoring a feature model. This framework enables users to perform automatic and semi-automatic refactoring on the feature model.Conclusions: Automated tool support for refactoring is a key issue for adopting approaches such as utilizing feature models and integrating them into the software development process of companies. In this work, we define some of the important refactoring rules on the feature model and provide tools that enable users to add new rules using the ATL M2M language. Our framework assesses the correctness of the refactorings using the Alloy language.

Reactive model transformation with ATL

Model-driven applications may maintain large networks of structured data models and transformations among them. The development of such applications is complicated by the need to reflect on the whole network any runtime update performed on models or transformation logic. If not carefully designed, the execution of such updates may be computationally expensive. In this paper we propose a reactive paradigm for programming model transformations, and we implement a reactive model-transformation engine. We argue that this paradigm facilitates the development of autonomous model-driven systems that react to update and request events from the host application by identifying and performing only the needed computation. We implement such approach by providing a reactive engine for the ATL transformation language. We evaluate the usage scenarios that this paradigm supports and we experimentally measure its ability to reduce computation time in transformation-based applications. • We propose a reactive paradigm for programming model transformations. • We implement a reactive model-transformation language by providing a reactive engine for the ATL transformation language. • We evaluate the usage scenarios that this paradigm supports. • We experimentally measure its ability to reduce computation time in transformation-based applications.

Formalised EMFTVM bytecode language for sound verification of model transformations

Model-driven engineering is an effective approach for addressing the full life cycle of software development. Model transformation is widely acknowledged as one of its central ingredients. With the increasing complexity of model transformations, it is urgent to develop verification tools that prevent incorrect transformations from generating faulty models. However, the development of sound verification tools is a non-trivial task, due to unimplementable or erroneous execution semantics encoded for the target model transformation language. In this work, we develop a formalisation for the EMFTVM bytecode language by using the Boogie intermediate verification language. It ensures the model transformation language has an implementable execution semantics by reliably prototyping the implementation of the model transformation language. It also ensures the absence of erroneous execution semantics encoded for the target model transformation language by using a translation validation approach.

Full contract verification for ATL using symbolic execution

The Atlas Transformation Language (ATL) is currently one of the most used model transformation languages and has become a de facto standard in model-driven engineering for implementing model transformations. At the same time, it is understood by the community that enhancing methods for exhaustively verifying such transformations allows for a more widespread adoption of model-driven engineering in industry. A variety of proposals for the verification of ATL transformations have arisen in the past few years. However, the majority of these techniques are either based on non-exhaustive testing or on proof methods that require human assistance and/or are not complete. In this paper, we describe our method for statically verifying the declarative subset of ATL model transformations. This verification is performed by translating the transformation (including features like filters, OCL expressions, and lazy rules) into our model transformation language DSLTrans. As we handle only the declarative portion of ATL, and DSLTrans is Turing-incomplete, this reduction in expressivity allows us to use a symbolic-execution approach to generate representations of all possible input models to the transformation. We then verify pre-/post-condition contracts on these representations, which in turn verifies the transformation itself. The technique we present in this paper is exhaustive for the subset of declarative ATL model transformations. This means that if the prover indicates a contract holds on a transformation, then the contract’s pre-/post-condition pair will be true for any input model for that transformation. We demonstrate and explore the applicability of our technique by studying several relatively large and complex ATL model transformations, including a model transformation developed in collaboration with our industrial partner. As well, we present our ‘slicing’ technique. This technique selects only those rules in the DSLTrans transformation needed for contract proof, thereby reducing proving time.

VMTL: a language for end-user model transformation

Model transformation is a key enabling technology of Model-Driven Engineering (MDE). Existing model transformation languages are shaped by and for MDE practitioners--a user group with needs and capabilities which are not necessarily characteristic of modelers in general. Consequently, these languages are largely ill-equipped for adoption by end-user modelers in areas such as requirements engineering, business process management, or enterprise architecture. We aim to introduce a model transformation language addressing the skills and requirements of end-user modelers. With this contribution, we hope to broaden the application scope of model transformation and MDE technology in general. We discuss the profile of end-user modelers and propose a set of design guidelines for model transformation languages addressing them. We then introduce Visual Model Transformation Language (VMTL) following these guidelines. VMTL draws on our previous work on the usability-oriented Visual Model Query Language. We implement VMTL using the Henshin model transformation engine, and empirically investigate its learnability via two user experiments and a think-aloud protocol analysis. Our experiments, although conducted on computer science students exhibiting only some of the characteristics of end-user modelers, show that VMTL compares favorably in terms of learnability with two state-of the-art model transformation languages: Epsilon and Henshin. Our think-aloud protocol analysis confirms many of the design decisions adopted for VMTL, while also indicating possible improvements.

Round-trip Engineering UML Class Models and Java Models

Model transformations constitute the key technology for model-driven software development, a software engineering discipline which became more and more important during the last decade. While tool support for unidirectional batch transformations is rather mature, bidirectional and incremental transformations are only weakly investigated. Nevertheless, several usage scenarios demand for incremental and bidirectional transformations, like round-trip engineering between UML class models and Java source code. This paper presents a bidirectional transformation between UML class models and a Java model which is obtained from Java source code. The transformation is written in QVT Relations, a declarative model transformation language provided by the OMG. While the case study demonstrates that it is possible to specify bidirectional transformations between heterogeneous metamodels in a single relational specification, it also reveals some inherent limitations of the language and the corresponding tool support.

PTL: A model transformation language based on logic programming

In this paper we present a model transformation language based on logic programming. The language, called PTL (Prolog based Transformation Language), can be considered as a hybrid language in which ATL (Atlas Transformation Language)-style rules are combined with logic rules for defining transformations. ATL-style rules are used to define mappings from source models to target models while logic rules are used as helpers. The implementation of PTL is based on the encoding of the ATL-style rules by Prolog rules. Thus, PTL makes use of Prolog as a transformation engine. We have provided a declarative semantics to PTL and proved the semantics equivalent to the encoded program. We have studied an encoding of OCL (Object Constraint Language) with Prolog goals in order to map ATL to PTL. Thus a subset of PTL can be considered equivalent to a subset of ATL. The proposed language can be also used for model validation, that is, for checking constraints on models and transformations. We have equipped our language with debugging and tracing capabilities which help developers to detect programming errors in PTL rules. Additionally, we have developed an Eclipse plugin for editing PTL programs, as well as for debugging, tracing and validation. Finally, we have evaluated the language with several transformation examples as well as tested the performance with large models.

Assessing and improving quality of QVTo model transformations

We investigate quality improvement in QVT operational mappings (QVTo) model transformations, one of the languages defined in the OMG standard on model-to-model transformations. Two research questions are addressed. First, how can we assess quality of QVTo model transformations? Second, how can we develop higher-quality QVTo transformations? To address the first question, we utilize a bottom---up approach, starting with a broad exploratory study including QVTo expert interviews, a review of existing material, and introspection. We then formalize QVTo transformation quality into a QVTo quality model. The quality model is validated through a survey of a broader group of QVTo developers. We find that although many quality properties recognized as important for QVTo do have counterparts in general purpose languages, a number of them are specific to QVTo or model transformation languages. To address the second research question, we leverage the quality model to identify developer support tooling for QVTo. We then implemented and evaluated one of the tools, namely a code test coverage tool. In designing the tool, code coverage criteria for QVTo model transformations are also identified. The primary contributions of this paper are a QVTo quality model relevant to QVTo practitioners and an open-source code coverage tool already usable by QVTo transformation developers. Secondary contributions are a bottom---up approach to building a quality model, a validation approach leveraging developer perceptions to evaluate quality properties, code test coverage criteria for QVTo, and numerous directions for future research and tooling related to QVTo quality.

A collaborative testbed web tool for learning model transformation in software engineering education

Software Engineering provides mechanisms to design, develop, manage and maintain social and collaborative software systems. At present, the Software Engineering Curricula includes teaching Model-Driven Engineering (MDE) as a new paradigm that enables higher productivity, attempting to maximize compatibility between systems. Modern learning methods MDE require the use of practical approaches to analyze new model-transformation techniques. Model transformations are carried out by using very high-level languages, like the ATL language. This model transformation language is built as a plugin for the Eclipse framework, and users who want to collaborate and develop software with it, have some difficulties executing ATL transformations outside this platform. To handle models at runtime, it is interesting to perform the transformations in a standalone way. In this context, we have developed a testbed web tool which aims to be useful for learning model transformation techniques. The tool offers a Graphical User Interface to test and verify the involved model transformations. The proposal is useful as a collaborative scenario for learning MDE and model transformation issues and techniques in Software Engineering education.

Model-Transformation Design Patterns

This paper defines a catalogue of patterns for the specification and design of model transformations, and provides a systematic scheme and classification of these patterns, together with pattern application examples in leading model transformation languages such as ATL, QVT, GrGen.NET, and others. We consider patterns for improving transformation modularization and efficiency and for reducing data storage requirements. We define a metamodel-based formalization of model transformation design patterns, and measurement-based techniques to guide the selection of patterns. We also provide an evaluation of the effectiveness of transformation patterns on a range of different case studies.

Least-change bidirectional model transformation with QVT-R and ATL

QVT Relations (QVT-R) is the standard language proposed by the OMG to specify bidirectional model transformations. Unfortunately, in part due to ambiguities and omissions in the original semantics, acceptance and development of effective tool support have been slow. Recently, the checking semantics of QVT-R has been clarified and formalized. In this article, we propose a QVT-R tool that complies to such semantics. Unlike any other existing tool, it also supports meta-models enriched with OCL constraints (thus avoiding returning ill-formed models) and proposes an alternative enforcement semantics that works according to the simple and predictable “principle of least change.” The implementation is based on an embedding of both QVT-R transformations and UML class diagrams (annotated with OCL) in Alloy, a lightweight formal specification language with support for automatic model finding via SAT solving. We also show how this technique can be applied to bidirectionalize ATL, a popular (but unidirectional) model transformation language.

A framework for model transformation verification

AbstractA model transformation verification task may involve a number of different transformations, from one or more of a wide range of different model transformation languages, each transformation may have a particular transformation style, and there are a number of different verification properties which can be verified for each language and style of transformation. Transformations may operate upon many different modelling languages. This diversity of languages and properties indicates the need for a suitably generic framework for model transformation verification, independent of particular model transformation languages, and able to provide support for systematic procedures for verification across a range of languages, and for a range of properties. In this paper we describe the elements of such a framework, and apply this framework to some example transformation verification problems. The paper is novel in covering a wide range of different verification techniques for a wide range of MT languages, within an integrated framework.

Dealing with Traceability in the MDDof Model Transformations

Traceability has always been acknowledged as a relevant topic in Software Engineering. However, keeping track of the relationships between the different assets involved in a development process is a complex and tedious task. The fact that the main assets handled in any model-driven engineering project are models and model transformations eases the task. In order to take advantage of this scenario, which has not been appropriately capitalized on by the most widely adopted model transformation languages before, this work presents MeTAGeM-Trace, a methodological and technical proposal with which to support the model-driven development of model transformations that include trace generation. The underlying idea is to start from a high-level specification of the transformation which is subsequently refined into lower-level transformation models in terms of a set of DSLs until the source code that implements the transformation can be generated. Running this transformation produces not only the corresponding target models, but also a trace model between the elements of the source and target models. As part of the proposal, an EMF-based toolkit has been developed to support the development of ATL and ETL model transformations. This toolkit has been empirically validated by conducting a set of case studies following a systematic research methodology.

An integrated framework for automated simulation of SysML models using DEVS

System models are constructed to design, study, and understand complex systems. According to the systems modeling language (SysML) that is a standard for model-based system engineering, all engineering activities should be performed using a common model. To validate complex system models defined in SysML, simulation is usually employed. There are numerous efforts to simulate SysML models using different simulation methods and tools. However, the efficient support of automated generation of executable simulation code is still an issue tangled by the research community. This paper introduces DEVSys, an integrated framework for utilizing existing SysML models and automatically producing executable discrete event simulation code, according to model driven architecture (MDA) concepts. Although this approach is not simulation-specific, discrete event system specification (DEVS) was employed, due to the similarities between SysML and DEVS, mainly in system structure description, and the mature, yet ongoing research on expressing executable DEVS models in a simulator-neutral manner. DEVSys framework elements include (a) a SysML profile for DEVS, enabling integration of simulation capabilities into SysML models, (b) a meta-model for DEVS, allowing the utilization of MDA concepts and tools, (c) a transformation of SysML models to DEVS models, using a standard model transformation language as query/view/transform (QVT), and (d) the generation of DEVS executable code for a DEVS simulation environment with an extensible markup language (XML) interface. The definition and implementation of DEVSys elements, as well as the process for its application are demonstrated and discussed, with the aid of a simple working example.

Metamodel Matching Techniques

During the last decade, Model Driven Engineering (MDE) has been proposed for supporting the development, maintenance and evolution of software systems. Model Driven Architecture (MDA), Software Factories and Eclipse Modeling Framework (EMF) are among the most representatives MDE approaches. Nowadays, it is well recognized that model transformation is at the heart of MDE approaches and, consequently represents one of the most important operations in MDE. However, despite the multitude of model transformation language proposals emerging from academic world and industry, these transformations are often manually specified; which is a tedious and error-prone task, and therefore an expensive process. Matching operation between metamodels is the keystone toward a (semi-)automatic transformation process. In this paper, the authors review metamodel matching techniques of the literature and then analyze their pros and cons in order to show how they can be useful for a semi-automatic transformation process. The result is a comparison of metamodel matching techniques, highlighting their similarities and differences in terms of information used for matching, demonstrating significant similarities between these techniques. Next, the authors compare four well-known metamodel matching techniques namely Similarity flooding, SAMT4MDE+ (extended Semi-Automatic Matching Tool for Model Driven Engineering), ModelCVS and AML (AtlanMod Matching Language) on ten couples of metamodels. For this comparison, the authors define a set of six criteria inspired from the database schema matching. One among these criteria is relevant to the quality of matching and for which we define a quality measure metrics. Furthermore, the authors develop a plug-in under Eclipse to support our comparison using ten couples of metamodels.

A Survey of Triple Graph Grammar Tools

Model transformation plays a central role in Model-Driven Engineer- ing (MDE) and supporting bidirectionality is a current challenge with important applications. Triple Graph Grammars (TGGs) are a formally founded, bidirectional model transformation language shown by numerous case studies to be promising and useful in practice. TGGs have been researched for more than 15 years and multiple TGG tools are under active development. Although a common theoreti- cal foundation is shared, TGG tools differ considerably concerning expressiveness, applicability, efficiency, and the underlying translation algorithm. There currently exists neither a quantitative nor a qualitative overview and comparison of TGG tools and it is quite difficult to understand the different foci and corresponding strengths and weaknesses. Our contribution in this paper is to develop a set of criteria for com- paring TGG tools and to provide a concrete quantitative and qualitative comparison of three TGG tools.

A demonstration-based model transformation approach to automate model scalability

An important aspect during software development is the ability to evolve and scale software models in order to handle design forces, such as enlarging and upgrading system features, or allocating more resources to handle additional users. Model scalability is the ability to refactor a base model, by adding or replicating the base model elements, connections or substructures, in order to build a larger and more complex model to satisfy new design requirements. Although a number of modeling tools have been developed to create and edit models for different purposes, mechanisms to scale models have not been well supported. In most situations, models are manually scaled using the basic point-and-click editing operations provided by the modeling environment. Manual model scaling is often tedious and error-prone, especially when the model to be scaled has hundreds or thousands of elements and the scaling process involves entirely manual operations. Although model scaling tasks can be automated by using model transformation languages, writing model transformation rules requires learning a model transformation language, as well as possessing a great deal of knowledge about the metamodel. Model transformation languages and metamodel concepts are often difficult for domain experts to understand. This requirement to learn a complex model transformation language exerts a negative influence on the usage of models by domain experts in software development. For instance, domain experts may be prevented from contributing to model scalability tasks from which they have significant domain experience. This paper presents a demonstration-based approach to automate model scaling. Instead of writing model transformation rules explicitly, users demonstrate how to scale models by directly editing the concrete model instances and simulate the model replication processes. By recording a user's operations, an inference engine analyzes the user's demonstration and generalizes model transformation patterns automatically, which can be reused to scale up other model instances. Using this approach, users are able to automate scaling tasks without learning a complex model transformation language. In addition, because the demonstration is performed on model instances, users are isolated from the underlying abstract metamodel definitions.

T-Core: a framework for custom-built model transformation engines

A large number of model transformation languages and tools have emerged since the early 2000s. A transformation engineer is thus left with too many choices for the language he use to perform a specific transformation task. Furthermore, it is currently not possible to combine or reuse transformations implemented in different languages. We therefore propose T-Core, a framework where primitive transformation constructs can be combined to define and encapsulate reusable model transformation idioms. In this context, the transformation engineer is free to use existing transformation building blocks from an extensible library or define his own transformation units. The proposed primitive transformation operators are the result of deconstructing different existing transformation languages. Reconstructing these languages offers a common basis to compare their expressiveness, provides a framework for inter-operating them, and allows the transformation engineer to design transformations with the most appropriate constructs for the task at hand.