DOCSLIB.ORG

Lazy Execution of Model-To-Model Transformations

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Lazy Execution of Model-To-Model Transformations Lazy Execution of Model-to-Model Transformations Massimo Tisi, Salvador Mart´ınez,Fr´ed´ericJouault, and Jordi Cabot AtlanMod, INRIA & Ecole´ des Mines de Nantes, France fmassimo.tisi, salvador.martinez perez, frederic.jouault, [email protected] Abstract. The increasing adoption of Model-Driven Engineering in in- dustrial contexts highlights scalability as a critical limitation of several MDE tools. Most of the current model-to-model transformation engines have been designed for one-shot translation of input models to output models, and present efficiency issues when applied to very large models. In this paper, we study the application of a lazy-evaluation approach to model transformations. We present a lazy execution algorithm for ATL, and we empirically evaluate a prototype implementation. With it, the elements of the target model are generated only when (and if) they are accessed, enabling also transformations that generate infinite target models. We achieve our goal on a significant subset of ATL by extending the ATL compiler. 1 Introduction Several Model-Driven Engineering (MDE) tools, when adopted in industrial con- texts, show critical effeciency limitations in handling very large models (VLMs). When these tools are built around model-to-model (M2M) transformations, the efficiency of the transformation engine risks to become a performance bottleneck for the whole MDE environment. While specific M2M transformation languages and engines have been developed since several years [12,8,3], optimizing the transformation of VLMs is just becoming a compelling research task. Lazy evaluation is one of the classical approaches that can provide, under specific conditions, a significant speed-up in program execution, especially when manipulating large data structures. When a programming language performs lazy evaluation, the value of an expression is calculated only when it is needed for a following computation (in contrast with eager evaluation, where expressions are evaluated as soon as they occur). This avoids the computation of unnecessary intermediate values. The useful part of large data structures is only calculated on-demand, even allowing for infinite-size data structures. For this reason lazy evaluation is a commonly used technique in several programming paradigms (for instance functional programming languages are classified in lazy or eager, depending on their evaluation strategy). Lazy evaluation would significantly speed-up the execution of MDE tools based on M2M transformations, e.g., in cases where only part of the VLMs 2 involved in the transformations is actually used. Unfortunately, all the M2M transformation engines we are aware of support only eager computation of the target models. Models are always completely generated according to the trans- formation logic and it is not possible to automatically avoid the computation of model elements that will not be consumed afterwards. This paper wants to provide the following contributions: 1) the study of the application of lazy evaluation to M2M transformation languages as a twofold problem, encompassing lazy navigation of the source model and lazy generation of the target model; 2) the implementation of an engine for lazy generation of the target model; 3) a practical evaluation of the lazy approach to model generation. Our approach has been implemented in a prototype of a lazy transformation engine for the ATL [8] language, obtained by adapting the standard ATL engine. Our experimentation shows that M2M transformation languages like ATL, with an explicit representation of the transformation logic, can be naturally provided with an efficient lazy evaluation strategy. Moreover, our approach to lazy generation allows the construction of an engine that can be plugged into existing tools consuming EMF models, without requiring modifications to the tools. The model is accessed like a normal EMF model, but its elements are computed on demand. Finally the lazy generation approach can be naturally applied to transfor- mations that generate an unbounded target model. Only the part of the model explicitly requested by the consumer is generated. In this way finite computa- tions can make use of infinite intermediate models generated by transformation. This represents a significant extension of the application space of existing trans- formation languages. The paper is structured as follows: Section 2 introduces the problems moti- vating the paper, by providing two running examples. Section 3 describes our approach to lazy execution of model transformations, in Section 4 we describe the implementation of a lazy engine for ATL and in Section 5 we experimentally evaluate its behavior; Section 6 discusses related work and, finally, in Section 7 we conclude the paper and propose further challenges. 2 Motivating Scenarios In this section we provide two application scenarios that are the motivation for our work, running examples of the paper and subject of our experimental evaluation. 2.1 Scenario 1: Large Models To illustrate how laziness addresses the performance problems of handling VLMs, we introduce an ideal database schema editor based on M2M transformations, whose structure is shown is Fig 1. This tool provides the user with an editor of the conceptual model of the database (in the form of a UML Class Diagram) 3 Fig. 1. A model-driven database schema editor. Fig. 2. Class and Relational metamodels. and with a transformation that generates a corresponding relational model. The user can check the relational model by using a read-only model browser. The tool uses a M2M transformation to generate the relational model from the Class diagram (the well-known Class2Relational transformation). In Fig. 2 we show the source and target metamodels of the transformation. The Class- Diagram metamodel represents a very simplified UML Class diagram. In this metamodel, Packages are containers of Classifiers that are either Datatypes or Classes. Classes can, in turn, be containers of Attributes, which can be multi- valued. The Relational metamodel describes simple relational schemas. Schema contains Tables that are composed of Columns. Finally, Columns have a type that characterizes the kind of elements they can hold. Listing 1.1 shows the main rules of the Class2Relational ATL transformation. Listing 1.1. ATL Class2Relational transformation. 1 2 rule Package2Schema f 3 from 4 p : ClassDiagram ! P a c k a g e 5 to 6 out : R e l a t i o n a l ! S c h e m a ( 7 ownedElements <− p . ownedElement −> 8 s e l e c t ( e j e . oclIsTypeOf ( ClassDiagram ! Class )) 9 ) 10 g 11 12 rule Class2Table f 13 from 14 c : ClassDiagram ! Class 15 to 16 out : R e l a t i o n a l ! Table ( 17 name <− c . name , 18 col <− Sequence f keyg−> 4 19 union ( c . attr−>s e l e c t ( e j not e . multiValued )), 20 key <− Set f key g 21 ), 22 key : R e l a t i o n a l ! C o l u m n ( 23 name <− 'objectId' , 24 type <− t h i s M o d u l e . objectIdType 25 ) 26 g 27 28 rule DataType2Type f 29 from 30 dt : ClassDiagram ! D a t a T y p e 31 to 32 out : R e l a t i o n a l ! Type ( 33 name <− dt . name 34 ) 35 g 36 37 rule DataTypeAttribute2Column f 38 from 39 a : ClassDiagram ! A t t r i b u t e ( 40 a . type . oclIsKindOf ( ClassDiagram ! D a t a T y p e ) and not a . multiValued 41 ) 42 to 43 out : R e l a t i o n a l ! C o l u m n ( 44 name <− a . name , 45 type <− a . type 46 ) 47 g 48 49 rule ClassAttribute2Column f 50 from 51 a : ClassDiagram ! A t t r i b u t e ( 52 a . type . oclIsKindOf ( ClassDiagram ! Class ) and 53 not a . multiValued 54 ) 55 to 56 f o r e i g n K e y : R e l a t i o n a l ! C o l u m n ( 57 name <− a . name + 'Id' , 58 type <− t h i s M o d u l e . objectIdType 59 ) 60 g The ATL transformation constitutes a set of rules that describe how parts of the input model generate parts of the target model. These rules must have an input pattern and an output pattern. E.g., in the rule ClassAttribute2Column input model elements of type Attribute are selected to be transformed into out- put elements of type Column. Rules can have filters and bindings. Filters are used to impose conditions on the input elements selected by the input pattern and bindings are used to initialize values of the elements created by the out- put pattern. In the rule ClassAttribute2Column, a filter is introduced to select only Attributes that are not multivalued and whose type is Class. Two bindings are then used to initialize the name and type of the created Column. The rule Class2Table creates a Table for each Class, adds a key Column and initializes the list of columns with the respectively transformed Attributes. Finally, rule Package2Schema transforms a Package into a relational Schema and initializes the list of Tables. The ATL transformation is executed in two steps. In the first step all the rules are matched creating all the corresponding target elements. Additionally, matching a rule creates, in the internal structures of the transformation engine, 5 Fig. 3. A model-driven visualizator for method-call trees. a traceability link that relates three components: the rule, the match (i.e. source elements) and the newly created target elements. In the second step, the created elements are initialized as described in the rule bindings. To perform the inizial- ization, ATL relies on a resolution algorithm that has been explained in details in [8]. Even with the very simple mapping of this scenario, when the Class dia- gram is large enough the transformation execution time can be significant.
Load more

Recommended publications
  • Model Transformation Languages Under a Magnifying Glass:A Controlled Experiment with Xtend, ATL, And
    CORE Metadata, citation and similar papers at core.ac.uk Provided by The IT University of Copenhagen's Repository Model Transformation Languages under a Magnifying Glass: A Controlled Experiment with Xtend, ATL, and QVT Regina Hebig Christoph Seidl Thorsten Berger Chalmers | University of Gothenburg Technische Universität Braunschweig Chalmers | University of Gothenburg Sweden Germany Sweden John Kook Pedersen Andrzej Wąsowski IT University of Copenhagen IT University of Copenhagen Denmark Denmark ABSTRACT NamedElement name : EString In Model-Driven Software Development, models are automatically processed to support the creation, build, and execution of systems. A large variety of dedicated model-transformation languages exists, Project Package Class StructuralElement modifiers : Modifier promising to efficiently realize the automated processing of models. [0..*] packages To investigate the actual benefit of using such specialized languages, [0..*] subpackages [0..*] elements Modifier [0..*] classes we performed a large-scale controlled experiment in which over 78 PUBLIC STATIC subjects solve 231 individual tasks using three languages. The exper- FINAL Attribute Method iment sheds light on commonalities and differences between model PRIVATE transformation languages (ATL, QVT-O) and on benefits of using them in common development tasks (comprehension, change, and Figure 1: Syntax model for source code creation) against a modern general-purpose language (Xtend). Our results show no statistically significant benefit of using a dedicated 1 INTRODUCTION transformation language over a modern general-purpose language. In Model-Driven Software Development (MDSD) [9, 35, 38] models However, we were able to identify several aspects of transformation are automatically processed to support creation, build and execution programming where domain-specific transformation languages do of systems.
    [Show full text]
  • The Viatra-I Model Transformation Framework Users' Guide
    The Viatra-I Model Transformation Framework Users’ Guide c 2007. OptXware Research and Development LLC. This document is property of the OptXware Research and Development LLC. To copy the whole or parts of it, or passing the contained information to third parties is allowed only with prior approval of OptXware Research and Development LLC. Contents 1 Introduction 6 1.1 The VIATRA Model Transformation Framework ... 6 1.1.1 Mission statement ................ 6 1.1.2 Target application domains ........... 6 1.1.3 The approach ................... 7 1.2 The Current Release ................... 7 1.2.1 Product features ................. 7 1.2.2 The Development Team ............. 9 2 Graphical User Interface of VIATRA 10 2.1 Initial Steps with Using VIATRA ............ 10 2.1.1 Installation .................... 10 2.1.2 Setting up the VIATRA environment in Eclipse 17 2.1.3 Creating a new project .............. 19 2.1.4 Creating a model space ............. 21 2.1.5 Opening and saving a model space ....... 23 2.1.6 Creating a metamodel or transformation .... 25 2.1.7 Parsing a metamodel or transformation .... 27 2.1.8 Executing a transformation ........... 31 2.2 Syntax for Format String in the Tree Editor ...... 32 2.2.1 Supported property names ........... 33 2.2.2 Examples ..................... 34 2 Contents 3 3 Writing Import Modules 36 3.1 Creating a meta model .................. 36 3.2 Handling concrete syntax ................ 37 3.3 Building up models .................... 38 3.4 Structure of an import plugin .............. 40 3.5 Installing a new importer ................ 42 4 Writing New Native Functions for VIATRA 43 4.1 Implementing a New Function .............
    [Show full text]
  • Expressive and Efficient Model Transformation with an Internal DSL
    Expressive and Efficient Model Transformation with an Internal DSL of Xtend Artur Boronat Department of Informatics, University of Leicester, UK [email protected] ABSTRACT 1 INTRODUCTION Model transformation (MT) of very large models (VLMs), with mil- Over the past decade the application of MDE technology in indus- lions of elements, is a challenging cornerstone for applying Model- try has led to the emergence of very large models (VLMs), with Driven Engineering (MDE) technology in industry. Recent research millions of elements, that may need to be updated using model efforts that tackle this problem have been directed at distributing transformation (MT). This situation is characterized by important MT on the Cloud, either directly, by managing clusters explicitly, or challenges [26], starting from model persistence using XMI serial- indirectly, via external NoSQL data stores. In this paper, we draw at- ization with the Eclipse Modeling Framework (EMF) [31] to scalable tention back to improving efficiency of model transformations that approaches to apply model updates. use EMF natively and that run on non-distributed environments, An important research effort to tackle these challenges was showing that substantial performance gains can still be reaped on performed in the European project MONDO [19] by scaling out that ground. efficient model query and MT engines, such as VIATRA[3] and We present Yet Another Model Transformation Language (YAMTL), ATL/EMFTVM [46], building on Cloud technology either directly, a new internal domain-specific language (DSL) of Xtend for defin- by using distributed clusters of servers explicitly, or indirectly, by ing declarative MT, and its execution engine.
    [Show full text]
  • A Framework for Model Transformation Verification LANO, Kevin, CLARK, T
    A framework for model transformation verification LANO, Kevin, CLARK, T. <http://orcid.org/0000-0003-3167-0739> and KOLAHDOUZ-RAHIMI, S. Available from Sheffield Hallam University Research Archive (SHURA) at: http://shura.shu.ac.uk/12046/ This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. Published version LANO, Kevin, CLARK, T. and KOLAHDOUZ-RAHIMI, S. (2015). A framework for model transformation verification. Formal Aspects of Computing, 27 (1), 193-235. Copyright and re-use policy See http://shura.shu.ac.uk/information.html Sheffield Hallam University Research Archive http://shura.shu.ac.uk A framework for verification of model transformations K. Lano, T. Clark, S. Kolahdouz-Rahimi Dept. of Informatics, King's College London; Dept. of Informatics, Middlesex University Abstract. A model transformation verification task may involve a number of different trans- formations, 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 transfor- mation. Transformations may operate upon many different modelling languages. This diver- sity 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 a range of transformation verification problems.
    [Show full text]
  • Model Transformation Design Patterns
    Model Transformation Design Patterns Hüseyin Ergin [email protected] Department of Computer Science, University of Alabama, U.S.A. Abstract. In this document, a brief overview of my doctoral research is pre- sented. In model-driven engineering (MDE), most problems are solved using model transformation. An efficient process to solving these problems is to apply reusable patterns while solving them. Finding reusable design patterns to specific subsets of problems helps to decrease the time and cost needed to solve them. My doctoral research is based on finding these design patterns to be applied on model transformation problems and evaluating them in terms of quality criteria. My next step is to generate these design pattern instances automatically by using higher-order transformation. 1 Introduction Model-driven engineering (MDE) [1] is considered a well-established software devel- opment approach that uses abstraction to bridge the gap between the problem and the software implementation. These abstractions are defined as models. Models are primary artifacts in MDE and are used to describe complex systems at multiple levels of abstrac- tion, while capturing some of their essential properties. These levels of abstraction let domain experts describe and solve problems without depending on a specific platform or programming language. Models are instances of a meta-model which defines the syntax of a modeling lan- guage. In MDE, the core development process consists of a series of transformations over models, called model transformation. Model transformations take models as input and output according to the specifications defined by the meta-model. In this document, I summarize the subject that I want to work on in my dissertation.
    [Show full text]
  • Model Transformation by Graph Transformation: a Comparative Study
    Model Transformation by Graph Transformation: A Comparative Study Gabriele Taentzer1, Karsten Ehrig1, Esther Guerra2, Juan de Lara3, Laszlo Lengyel4, Tihamer Levendovszky4, Ulrike Prange1, Daniel Varro4, and Szilvia Varro-Gyapay4 1 Technische Universit¨atBerlin, Germany {karstene,gabi,ullip}@cs.tu-berlin.de 2 Universidad Carlos III de Madrid, Spain [email protected] 3 Universidad Autonoma de Madrid, Spain [email protected] 4 Budapest University of Technology and Economics, Hungary {varro,gyapay}@mit.bme.hu {lengyel,tihamer}@aut.bme.hu Abstract. Graph transformation has been widely used for expressing model transformations. Especially transformations of visual models can be naturally formulated by graph transformations, since graphs are well suited to describe the underlying structures of models. Based on a com- mon sample model transformation, four different model transformation approaches are presented which all perform graph transformations. At first, a basic solution is presented and crucial points of model transforma- tions are indicated. Subsequent solutions focus mainly on the indicated problems. Finally, a first comparison of the chosen approaches to model transformation is presented where the main ingredients of each approach are summarized. 1 Introduction Raising the abstraction level from textual programming languages to visual mod- eling languages, model transformation techniques and tools have become more focused recently. Model transformation problems can be formulated as graph transformation problems, thus, a variety of tools choose this technique as the underlying mechanism for the transformation engine. This paper aims at com- paring four approaches to model transformation that apply graph transforma- tion techniques for model transformation. These can be characterized by their tool support. The presented tools are AGG [1], AToM3 [15], VIATRA2 [25] and VMTS [26] [16].
    [Show full text]
  • Model Transformations
    Model Transformations Modelling with UML, with semantics 271 What is a transformation? • A transformation is the automatic generation of a target model from a source model, according to a transformation definition. • A transformation definition is a set of transformation rules that together describe how a model in the source language can be transformed into a model in the target language. • A transformation rule is a description of how one or more constructs in the source language can be transformed into one or more constructs in the target language. • Unambiguous specifications of the way that (part of) one model can be used to create (part of) another model • Preferred characteristics of transformations • semantics-preserving Modelling with UML, with semantics 272 Model-to-model vs. Model-to-code • Model-to-model transformations Model ModelModel Meta-model • Transformations may be between different languages. In particular, between different languages defined by MOF Transformation Transformer Rules • Model-to-text transformations Model Meta-model • Special kind of model to model transformations optional, can be repeated • MDA TS to Grammar TS Code Transformer Generation Templates Manually Generated Code Written Code optional Modelling with UML, with semantics 273 Transformations as models • Treating everything as a model leads not only to conceptual simplicity and regular architecture, but also to implementation efficiency. • An implementation of a transformation language can be composed of a transformation virtual machine plus a metamodel-driven compiler. • The transformation VM allows uniform access to model and metamodel elements. MMa MMt MMb Ma Mt Mb Transformation Virtual Machine Modelling with UML, with semantics 274 Model transformation • Each model conforms to a metamodel.
    [Show full text]
  • The MT Model Transformation Language
    The MT model transformation language Laurence Tratt Department of Computer Science, King's College London, Strand, London, WC2R 2LS, U.K. [email protected] ABSTRACT the MT model transformation language, outlining its basic Model transformations are recognised as a vital part of Mo- features, along with some of the additional features it pos- del Driven Development, but current approaches are often sesses over existing approaches such as the QVT-Partners simplistic, with few distinguishing features, and frequently approach [11], and concluding with a non-trivial example lack an implementation. The practical difficulties of im- of its use. MT is implemented as a Domain Specific Lan- plementing an approach inhibit experimentation within the guage (DSL) within the Converge programming language paradigm. In this paper, I present the MT model trans- [12]. Converge is a novel Python-derived programming lan- formation language which was implemented as a low-cost guage whose syntax can be extended, allowing DSLs to be DSL in the Converge programming language. Although MT directly embedded within it. Some of MT's differences from shares several aspects in common with other model trans- other approaches are a side-effect of implementing MT as a formation languages, an ability to rapidly experiment with Converge DSL; some are the result of experimentation with a the implementation has led MT to contain a number of new concrete, but malleable, implementation. Space constraints features, insights and differences from other approaches. mean that it is left to an extended technical report to de- tail MT's complete implementation [14]. Due partly to its implementation as a Converge DSL, MT is novel due to its 1.
    [Show full text]
  • Modeling Transformations Using QVT Operational Mappings P.J
    Modeling transformations using QVT Operational Mappings P.J. Barendrecht SE 420606 Research project report Supervisor: prof.dr.ir. J.E. Rooda Coaches: dr.ir. R.R.H. Schiffelers dr.ir. D.A. van Beek Eindhoven University of Technology Department of Mechanical Engineering Systems Engineering Group Eindhoven, April 2010 Summary Models play an increasingly important role in the development of (software) systems. The methodology to develop systems using models is called Model-Driven Engineering (MDE). One of the key aspects of MDE is transforming models to other models. These transformations are specified in the problem domain. Unlike coding a transformation in the implementation domain, MDE uses different abstraction levels to model a transfor- mation. The transformation is based on the languages of the source- and target models. In the problem domain, such a language is usually called a meta-model. A model is an instance of a meta-model when it conforms to the specifications of the meta-model. Fi- nally, the meta-model itself conforms to a higher abstraction level, the metameta-model. With the help of the metameta-model Ecore, simple meta-models are designed to ex- periment with the meta-model of the transformation, the Domain Specific Language Query/View/Transformation (QVT) specified by OMG. In other words, QVT is the language used to model transformations. The syntax and semantics of the QVT variant Operational Mappings, often named QVTo, are investigated in this report. The different aspects of the language are explained and illustrated by examples. After the explanation of QVTo, this knowledge is applied to solve a more difficult transformation.
    [Show full text]
  • Reusing Platform-Specific Models in Model-Driven Architecture for Software Product Lines
    Reusing Platform-specific Models in Model-Driven Architecture for Software Product Lines Fred´ eric´ Verdier1,2, Abdelhak-Djamel Seriai1 and Raoul Taffo Tiam2 1LIRMM, University of Montpellier / CNRS, 161 rue Ada, 34095, Montpellier, France 2Acelys Informatique, Business Plaza bat.ˆ 3 - 159 rue de Thor, 34000, Montpellier, France Keywords: Reuse, Model-Driven Architecture, Software Product Line, Variability, Platform-specific Model. Abstract: One of the main concerns of software engineering is the automation of reuse in order to produce high quality applications in a faster and cheaper manner. Model-Driven Software Product Line Engineering is an approach providing solutions to systematically and automatically reuse generic assets in software development. More specifically, some solutions improve the product line core assets reusability by designing them according to the Model-Driven Architecture approach. However, existing approaches provide limited reuse for platform- specific assets. In fact, platform-specific variability is either ignored or only partially managed. These issues interfere with gains in productivity provided by reuse. In this paper, we first provide a better understanding of platform-specific variability by identifying variation points in different aspects of a software based on the well-known ”4+1” view model categorization. Then we propose to fully manage platform-specific variability by building the Platform-Specific-Model using two sub- models: the Cross-Cutting Model, which is obtained by transformation of the Platform-Independent Model, and the Application Structure Model, which is obtained by reuse of variable platform-specific assets. The approach has been experimented on two concrete applications. The obtained results confirm that our approach significantly improves the productivity of a product line.
    [Show full text]
  • A Model Transformation in Model Driven Architecture from Business Model to Web Model
    IAENG International Journal of Computer Science, 45:1, IJCS_45_1_16 ______________________________________________________________________________________ A Model Transformation in Model Driven Architecture from Business Model to Web Model Yassine Rhazali, Youssef Hadi, Idriss Chana, Mohammed Lahmer, and Abdallah Rhattoy related to a target platform. In practice, automatic Abstract— The models transformation is the fundamental transformation begins from PIM to PSM. However, our key in Model Driven Architecture approach. In Model Driven ultimate aim is to make the CIM a productive level, and a Architecture there are two transformations kinds: the CIM to basis for building PIM through an automatic transformation. PIM transformation and the PIM to PSM transformation. The researchers focused on the transformation from PIM level to The goal is that business models do not remain only simple PSM level, because there are several points in common between documents of communication between business experts and these two levels. However, the transformation from CIM level software designers. to PIM level is rarely discussed in research subjects because In this paper, we present a solution for automating they are two completely different levels. This paper proposes a transformation from CIM level business-based to the PIM model transformation method to master the transformation level web-based. However, we use UML 2 activity diagram from CIM to PIM web-based in accordance with the Model Driven Architecture approach. Indeed, the main value of this to attain concentrated CIM models, which simplifies the method is to propose a transformation from business-oriented transformation to PIM level. Then, we define a set of models to web-oriented models. This method is founded on selected-rules for automating the transformation from CIM building a good CIM level via well-defined rules, allowing us to to PIM.
    [Show full text]
  • QVT Traceability: What Does It Really Mean?
    QVT Traceability: What does it really mean? Edward D. Willink1 and Nicholas Matragkas2 1 Willink Transformations Ltd., UK, ed-at-willink.me.uk 2 University of York, UK, nicholas.matragkas-at-york.ac.uk Abstract. Traceability in Model Transformation languages supports not only post-execution analysis, but also incremental update and co- ordination of repetition. The Query/View/Transformation family of lan- guages specify a form of traceability that unifies high and low level ab- straction in declarative and imperative transformation languages. Un- fortunately this aspect of the QVT specification is little more than an aspiration. We identify axioms that resolve the conflicting requirements on traceability, and provide a foundation for resolving further issues re- garding equality, transformation extension and mapping refinement. Keywords: Model Transformation, QVT, Traceability, Transformation Extension, Mapping Refinement 1 Introduction The successes of early model transformation prompted the Object Management Group (OMG) to issue a Request for Proposal for a standard solution to the problems of querying, viewing and transforming models. The initial submissions eventually converged to give us the Query/View/Transformation (QVT) family of languages. The specification standardizes research work and so the specifica- tion is imperfect. Problems in the specification are recorded as issues that can be raised by anyone at http://www.omg.org/report_issue.htm. The issues are addressed by a Revision Task Force (RTF) that proposes and votes on resolutions. The QVT 1.2 RTF has just completed resolutions for the 125 outstanding issues against QVT 1.1[9]. At the time of writing 2/3 have been balloted successfully, with the remaining 1/3 being voted on.
    [Show full text]