Transformation Language Research Articles

On the use of model transformation for the automation of product derivation process in SPL

Abstract Product Derivation represents one of the main challenges that Software Product Line (SPL) faces. Deriving individual products from shared software assets is a time-consuming and an expensive activity. In this paper, we (1) present an MDE approach for engineering SPL and (2) propose to leverage model-to-model transformations (MMT) and model-to-text (MTT) transformations for supporting both domain engineering and application engineering processes. In this work, we use ATL as a model-to-model transformation language and Acceleo as a model-to-text transformation language.The proposed approach is discussed with e-Health product line applications.

Transformation of Alloy Notation into a Semantic Notation

Transformation of a model based on first-order logic to a model that provides semantic notations is helpful necessary during the analysis phase of any proposed software. The semantic notations often guide the designer to develop pseudocode correctly. This study focuses on facilitation of transformation of one formal model, i.e., Alloy into another, i.e., OWL. The proposed approach extends the concept of existing techniques i.e., UML2Alloy and TwoUse to transform Alloy model into OWL. UML2Alloy transforms UML model into Alloy model, whereas TwoUse approach bridges the gap between UML model and OWL model. Alloy2OWL is based on metamodel-based transformation techniques, which help to map source model, i.e., Alloy into target model, i.e., OWL. For the proper explanation of this study, a model transformation framework is presented, which can be applied to other transformation languages. The proposed approach utilizes the Model-Driven Development techniques to deal with the analysis of Alloy model and determines design problems within a specification. In this paper, various challenges are also presented which occur during the transformation of Alloy to OWL.

Incremental execution of model-to-text transformations using property access traces

Automatic generation of textual artefacts (including code, documentation, configuration files, build scripts, etc.) from models in a software development process through the application of model-to-text (M2T) transformation is a common MDE activity. Despite the importance of M2T transformation, contemporary M2T languages lack support for developing transformations that scale with the size of the input model. As MDE is applied to systems of increasing size and complexity, a lack of scalability in M2T transformation languages hinders industrial adoption. In this paper, we propose a form of runtime analysis that can be used to identify the impact of source model changes on generated textual artefacts. The structures produced by this runtime analysis, property access traces, can be used to perform efficient source-incremental transformation: our experiments show an average reduction of 60% in transformation execution time compared to non-incremental (batch) transformation.

A survey of model transformation design patterns in practice

Model transformation design patterns have been proposed by a number of researchers, but their usage appears to be sporadic and sometimes patterns are applied without recognition of the pattern. In this paper we provide a systematic literature review of transformation design pattern applications. We evaluate how widely patterns have been used, and how their use differs in different transformation languages and for different categories of transformation. We identify what benefits appear to arise from the use of patterns, and consider how the application of patterns can be improved. The paper also identifies several new patterns which have not previously been catalogued.

Survey and classification of model transformation tools

Model transformation lies at the very core of model-driven engineering, and a large number of model transformation languages and tools have been proposed over the last few years. These tools can be used to develop, transform, merge, exchange, compare, and verify models and metamodels. In this paper, we present a comprehensive catalog of existing metamodel-based transformation tools and compare them using a qualitative framework. We begin by organizing the 60 tools we identified into a general classification based on the transformation approach used. We then compare these tools using a number of particular facets, where each facet belongs to one of six different categories and may contain several attributes. The results of the study are discussed in detail and made publicly available in a companion website with a capability to search for tools using the specified facets as search criteria. Our study provides a thorough picture of the state-of-the-art in model transformation techniques and tools. Our results are potentially beneficial to many stakeholders in the modeling community, including practitioners, researchers, and transformation tool developers.

Automatic transformation tools of UML design models from virtual prototypes of multi-jointed robots

Most of robotic companies develop a control programming of multi-jointed robots, which spend too much time to manually adjust the moving functions of the robots. To solve this problem, we adapt the virtual prototyping (VP) to develop the control program of the robotic behaviors. For software engineers, in order for them to easily program this robot, we also apply metamodel mechanism to convert UML models with virtual prototyping model. We propose the automatic model transformation from the virtual prototyping model to UML models, which will then develop coding based on UML models. To prove our mechanism’s efficiency, we implement Robot to UML Translator (RUT) as our transformation rules with ATLAS transformational language. Lastly, we show experimental validation about the consistency of our proposed technique with an example of multi-joined robot prototype models.

Influence of programming style in transformation bad smells: mining of ETL repositories

ABSTRACTBad smells affect maintainability and performance of model-to-model transformations. There are studies that define a set of transformation bad smells, and some of them propose techniques to recognize and – according to their complexity – fix them in a (semi)automated way. In academia it is necessary to make students aware of this subject and provide them with guidelines to improve the quality of their transformations. This paper presents the most common bad smells made by master students from Universidad de los Andes, and compares them with those from publicly available repositories of Epsilon transformation language transformations, with the purpose of knowing whether programming style affects the incidence of smells. Three concrete contributions are presented: (i) two new bad smells that enrich the existing catalogs; (ii) a process that includes the automated extraction of transformation metrics and bad smells metrics from the repositories, and a statistical analysis that helps in identifying the relation between such metrics; and (iii) a tool that automatizes the process. From the statistical analysis, we conclude that, students must be encouraged and guided to develop maintainable declarative transformations. At this point, our tool has been proved to be very useful to help improve the quality of students’ transformations.

Foundry: a message-oriented, horizontally scalable ETL system for scientific data integration and enhancement.

Data generated by scientific research enables further advancement in science through reanalyses and pooling of data for novel analyses. With the increasing amounts of scientific data generated by biomedical research providing researchers with more data than they have ever had access to, finding the data matching the researchers' requirements continues to be a major challenge and will only grow more challenging as more data is produced and shared. In this paper, we introduce a horizontally scalable distributed extract-transform-load system to tackle scientific data aggregation, transformation and enhancement for scientific data discovery and retrieval. We also introduce a data transformation language for biomedical curators allowing for the transformation and combination of data/metadata from heterogeneous data sources. Applicability of the system for scientific data is illustrated in biomedical and earth science domains.

Moving in the Spirit: Called to Transforming Discipleship: Reflections from the Vantage Points of the Marginalized People

Abstract“Mission from the margins” is neither a mere perspectival approach nor an option but an inevitable way of being church in God's mission. Likewise, the marginalized people are neither a broad category of people on the fringes of the society nor mere objects of charity and victims of circumstances. They are prophets and pathfinders indicting the world for its injustice through their lives of suffering and striving for its transformation through their struggles. As signs of hope testifying to the movement of the Spirit amidst despair and death, they help us to see God's mission not as a mere religious activity but as a spirituality of resistance and transformation for the sake of life and God's world. Reclaiming discipleship from the vantage of the marginalized, therefore, offers an opportunity for the churches to rediscover themselves afresh from being mere communities of believers and power structures to networks of partners for God's justice, participating in the larger struggles for the transformation of the world. As the gospels tell us, Jesus did not commission his disciples to call people to a belief system but to a covenantal relationship through a vocation of striving for the realization of God's reign. Such a sense of vocation is possible only when there is a radical change in Christian self‐understanding. It involves, first, interrogating and reimagining the ways in which churches affirm and practise their faith; second, leaving aside their captivity to certain belief systems and turning toward Jesus of Nazareth to teach the way – to be active partners with God rather than being passive believers; third, appropriating discipleship beyond the language and sphere of transformation of persons; and fourth, learning from and being enriched by the visions and resources of the marginalized in living out the call to be one in God's mission of transformation of the world.

F-Alloy: a relational model transformation language based on Alloy

Model transformations are one of the core artifacts of a model-driven engineering approach. The relational logic language Alloy has been used in the past to verify properties of model transformations. In this paper we introduce the concept of functional Alloy modules. In essence a functional Alloy module can be viewed as an Alloy module representing a model transformation. We describe a sublanguage of Alloy called F-Alloy specifically designed to concisely specify functional Alloy modules. The restrictions on F-Alloy’s syntax are meant to allow efficient execution of the specified transformation, without the use of backtracking, by an adapted interpretation algorithm. F-Alloy’s semantics is given in this paper as a direct translation to Alloy; hence, F-Alloy specifications are also analyzable using the powerful automatic analysis features of Alloy.

Generated PSM Web Model for E-learning Platform Respecting n-tiers Architecture

E-learning, or learning via a computer or mobile device, is growing. It can take many forms, such as an annotated PowerPoint presentation, a tutorial, or an interactive role-playing game .The possibilities are endless.
 Today, 80% of companies and communities have done a number of interesting and effective e-learning solutions, and 30% of all professional training are e-learning courses. The development of these platforms is based mainly on different technologies. This technological diversity can make comparing or managing E-learning platforms difficult, and the choice of a given platform will be also complex. Therefore, to address this problem, this paper proposes a solution to generate a PSM model based on n-tier architecture from a PIM model. The language used is the QVT (Query View Transformation) transformation language.

Model Transformation Modularization as a Many-Objective Optimization Problem

Model transformation programs are iteratively refined, restructured, and evolved due to many reasons such as fixing bugs and adapting existing transformation rules to new metamodels version. Thus, modular design is a desirable property for model transformations as it can significantly improve their evolution, comprehensibility, maintainability, reusability, and thus, their overall quality. Although language support for modularization of model transformations is emerging, model transformations are created as monolithic artifacts containing a huge number of rules. To the best of our knowledge, the problem of automatically modularizing model transformation programs was not addressed before in the current literature. These programs written in transformation languages, such as ATL, are implemented as one main module including a huge number of rules. To tackle this problem and improve the quality and maintainability of model transformation programs, we propose an automated search-based approach to modularize model transformations based on higher-order transformations. Their application and execution is guided by our search framework which combines an in-place transformation engine and a search-based algorithm framework. We demonstrate the feasibility of our approach by using ATL as concrete transformation language and NSGA-III as search algorithm to find a trade-off between different well-known conflicting design metrics for the fitness functions to evaluate the generated modularized solutions. To validate our approach, we apply it to a comprehensive dataset of model transformations. As the study shows, ATL transformations can be modularized automatically, efficiently, and effectively by our approach. We found that, on average, the majority of recommended modules, for all the ATL programs, by NSGA-III are considered correct with more than 84 percent of precision and 86 percent of recall when compared to manual solutions provided by active developers. The statistical analysis of our experiments over several runs shows that NSGA-III performed significantly better than multi-objective algorithms and random search. We were not able to compare with existing model transformations modularization approaches since our study is the first to address this problem. The software developers considered in our experiments confirm the relevance of the recommended modularization solutions for several maintenance activities based on different scenarios and interviews.

Model clone detection for rule-based model transformation languages

Cloning is a convenient mechanism to enable reuse across and within software artifacts. On the downside, it is also a practice related to severe long-term maintainability impediments, thus generating a need to identify clones in affected artifacts. A large variety of clone detection techniques have been proposed for programming and modeling languages; yet no specific ones have emerged for model transformation languages. In this paper, we explore clone detection for rule-based model transformation languages, including graph-based ones, such as Henshin, and hybrid ones, such as ATL. We introduce use cases for such techniques in the context of constructive and analytical quality assurance, and a set of key requirements we derived from these use cases. To address these requirements, we describe our customization of existing model clone detection techniques: We consider eScan, an a-priori-based technique, ConQAT, a heuristic technique, and a hybrid technique based on a combination of eScan and ConQAT. We compare these techniques in a comprehensive experimental evaluation, based on three realistic Henshin rule sets, and a comprehensive body of examples from the ATL transformation zoo. Our results indicate that our customization of ConQAT enables the efficient detection of the considered clones, without sacrificing accuracy. With our contributions, we present the first evidence on the usefulness of model clone detection for the quality assurance of model transformations and pave the way for future research efforts at the intersection of model clone detection and model transformation.

Change propagation and bidirectionality in internal transformation DSLs

Despite good results in several industrial projects, model-driven engineering (MDE) has not been widely adopted in industry. Although MDE has existed for more than a decade now, the lack of tool support is still one of the major problems, according to studies by Staron and Mohaghegi (Staron, in: Model driven engineering languages and systems, Springer, Berlin, 2006; Mohagheghi et al. in Empir Softw Eng 18(1):89–116, 2013). Internal languages offer a solution to this problem for model transformations, which are a key part of MDE. Developers can use existing tools of host languages to create model transformations in a familiar environment. These internal languages, however, typically lack key features such as change propagation or bidirectional transformations. In our opinion, one reason is that existing formalisms for these properties are not well suited for textual languages. In this paper, we present a new formalism describing incremental, bidirectional model synchronizations using synchronization blocks. We prove the ability of this formalism to detect and repair inconsistencies and show its hippocraticness. We use this formalism to create a single internal model transformation language for unidirectional and bidirectional model transformations with optional change propagation. In total, we currently provide 18 operation modes based on a single specification. At the same time, the language may reuse tool support for C#. We validate the applicability of our language using a synthetic example with a transformation from finite state machines to Petri nets where we achieved speedups of up to multiple orders of magnitude compared to classical batch transformations.

A Model Driven Architecture Approach to Generate Multidimensional Schemas of Data Warehouses

Over the past decade, the concept of data warehousing has been widely accepted. The main reason for building data warehouses is to improve the quality of information in order to achieve specific business objectives such as competitive advantage or improved decision-making. However, there is no formal method for deriving a multidimensional schema from heterogeneous databases that is recognized as a standard by the OMG and the professionals of the field. Which is why, in this paper, we present a model-driven approach (MDA) for the design of data warehouses. To apply the MDA approach to the Data warehouse construction process, we describe a multidimensional meta-model and specify a set of transformations from a UML meta-model which is mapped to a multidimensional meta-model. The execution of the transformation, programmed by the Query View Transformation (QVT) language, takes as input an instance of the UML Meta-Model to generate an instance of the Dimensional Meta-Model as output.

Transformative Language in the Desert: A review of Moses: A Human Life, by Avivah Gottleib Zornberg

Transformative Language in the Desert: A review of <i>Moses: A Human Life</i>, by Avivah Gottleib Zornberg

Walking Where Jesus Walked: American Christians and Holy Land Pilgrimage. By Hillary Kaell. New York: NYU Press, 2014. Pp. xiii+269. $28.00 (paper).

<i>Walking Where Jesus Walked: American Christians and Holy Land Pilgrimage</i>. By Hillary Kaell. New York: NYU Press, 2014. Pp. xiii+269. $28.00 (paper).

Translation of ATL to AGT and application to a code generator for Simulink

Analysing and reasoning on model transformations has become very relevant for various applications such as ensuring the correctness of transformations. ATL is a model transformation language with rich semantics and a focus on usability, making its analysis not straightforward. Conversely, algebraic graph transformation (AGT) is an approach with strong theoretical foundations allowing for formal analyses that would be valuable in the context of ATL. In this paper, we propose a translation of ATL to the AGT framework in the objective of bringing theoretical analyses of AGT to ATL transformations. We show that this transformation supports a sufficient subset of ATL to be used on an industrial application example: QGen, a qualifiable Simulink\(^{\circledR }\) to source code generator developed at AdaCore. In addition to this example, we validate our proposal by translating a set of feature-rich ATL transformations to the Henshin AGT framework. We execute the ATL and AGT versions on the same set of models and verify that the result is the same.

Theories of Transformative Learning in Jewish Education: Three Cases

ABSTRACTWe frequently encounter the claim that a particular Jewish educational experience will be “transformative” for the participants. The language may be hyperbole. But it may also point to educators’ aspirations to affect not just knowledge and practice but character and identity. In order to understand this phenomenon—not the phenomenon of the use of the language of transformation, per se, but the phenomenon of aspirational Jewish educational programs—this article develops three case studies (Encounter, the Bronfman Fellowship, and the Wexner Heritage Program). What emerges from these cases is a set of models or theories of transformative change: the Maimonides model, learning a habit such that, over time, habit becomes character; the paradise-and-exile model, becoming a seeker after an ideal that one has glimpsed; and the outsider-to-insider model, moving from a sense of fraudulence to a sense of confidence within a particular domain.

DERIVATIVE PROCESSES IN SPONTANEOUS YOUTH SPEECH (BASED ON MATERIAL OF KYIV)

The article revealed the basic ways of usual and occasional derivation in the everyday Kyiv youth speech on the basis of spontaneous speech texts analysis. The youth derivation demonstrates the impact on youth language of foreign languages, transformation and reinterpretation by the young generation of common lexicon and slang. Derivative processes in the youth speech tend to upgrading Ukrainian lexicon of everyday colloquial speech. Analysis of youth word formation can be continued by expanding the amount of material, considering the socio-political factors in the formation of new words and comparing the results with researches of the same processes in the other social groups’ speech.