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Automatic Generation of Model Traversals from Metamodel Definitions

Jožef Stefan Institute , Ljubljana, Slovenia. Automatic Generation of Model Traversals from Metamodel Definitions. Authors : Tomaž Lukman, Marjan Mernik, Zekai Demirezen , Barrett Bryant , Jeff Gray. ACM SE ‘10, Oxford, MS, 4/17/2010. 2/18. Agenda. Introduction Research problem

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Automatic Generation of Model Traversals from Metamodel Definitions

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  1. Jožef Stefan Institute, Ljubljana, Slovenia Automatic Generation of Model Traversalsfrom Metamodel Definitions Authors: Tomaž Lukman, Marjan Mernik, Zekai Demirezen, BarrettBryant, JeffGray ACM SE ‘10, Oxford, MS, 4/17/2010

  2. 2/18 Agenda • Introduction • Research problem • Research objectives • Related work • Proposed approach • Specification of semantics • Model traversal algorithm • Example • Conclusion

  3. 3/18 Introduction • Modeling is an important part of software engineering • Model-Driven Engineering (MDE) promotes the systematic and disciplined use of precise models throughout the software lifecycle • Increases productivity and software quality • Domain-Specific Modeling Languages (DSMLs) – use concepts (e.g., terms, symbols and pictures) and abstractions that are common to a specific domain • MDE needs tool support to enable various development tasks with a specific DSML • model editor, model debugger, test suite, interpreters • Without tool support a DSML can become obsolete

  4. 4/18 Model-Driven Engineering (MDE) • MDE: specifies and generates software systems based on high-level models • Domain-Specific Modeling (DSM): a paradigm of MDE that uses notations and rules from an application domain • Metamodel: defines a Domain-specific Modeling language (DSML) by specifying the entities and their relationships in an application domain • Model: an instance of the metamodel • Model Transformation: a process that converts one or more models to various levels of software artifacts (e.g., other models, source code)

  5. 5/18 Research problem • DSMLs are not defined precisely • The potential benefits of MDE cannot be achieved • Semantics are the most challenging part of a DSML definition • State-of-the-practice: semantics are specified with model interpreters • Low understandability • Model-based tools cannot be automatically generated (e.g., code interpreters, debuggers) • Manual development of model-based tools is time consuming, error prone and expensive • Challenge: How to generate model based tools automatically?

  6. 6/18 Research objectives • Analogy: in the field of programming languages, language-based tools can be automatically generated • E.g., attribute grammars -> debuggers, animators, test suites • Broad objective: Development of a formalism for semantics from which model based tools can be automatically generated • Current work: The generation of model interpreters • What is needed for the generation of model interpreters: • A formalism to specify the semantics • An algorithm to traverse the model and generate the parser

  7. 7/18 Semantics specification for modeling languages • State-of-the-art: several proposals for specifying the semantics of modeling languages already exist • Translation semantics: semantics are defined trough a mapping into formalism with well-known semantics (e.g., Abstract State Machines) • Drawback: backward mapping of computation results • Weaving behavior: an action language specifies the bodies of the operations in the metamodel • Drawback: action languages are imperative • Semantics based on rewriting systems: operational approach for defining through rewrite rules e.g., graph grammars • Issue: None of the proposed approaches focuses on the automatic generation of model-based tools

  8. 8/18 Proposed approach • Idea: extend metamodels with semantic information • Similar to attribute grammars in programming languages • Consists of two parts: • Information about semantics in the metamodel = specification of semantics • Automatic synthesis of this information to generate model based tools = traversal algorithm

  9. 9/18 Specification of semantics • The semantics is specified with semantic attributes and semantic rules • Semantic attribute – associate with eachmetaclass • Semantic rules - carry semantic information that specifies how semantic attributes are calculated • Currently specified through Java   • The meaning of the model will be obtained by evaluating attribute occurrences • The initial value of the attribute is undefined • Redefined by the traversal algorithm during its execution • They are used to obtain/compute the meaning of the whole model

  10. 10/18 Model traversal algorithm • A traversal algorithm over models (graphs) is needed to evaluating semantics attributes based on semantic rules • The algorithm depends on the metamodel and the API (application programming interface) of the model repository • Example of modeling environments: • GME (Generic Modeling Environment) • GMF (Graphical Modeling Framework) • We developed an initial algorithm that works with EMF (Eclipse Modeling Framework) • Optimized and extended to other environments in the future • The development of the traversal algorithm represents the most challenging part of our approach

  11. 11/18 Development of the model traversal algorithm (1/3) • The requirements for the model traversal algorithm: • All model elements should be visited • Avoidance of endless loops • It must find the start element of the model • Executabiltiy on disconnected models (there are some modes that are not connected to other nodes)

  12. 12/18 Development of the model traversal algorithm (2/3) • Interpreters are developed based on the metamodel nodes and relationships between them • We specified: what the algorithm should do (i.e., where to navigate) when a specific relationship occurs • The types of relationships in Ecore (EMFs metamodeling language): • Root metaclass – traverse all traversable relationships • Unidirectional metarelationship – traverse into one direction (where arrow is pointing) • Bidirectional metarelationship – traverse in both ways

  13. 13/18 Development of the model traversal algorithm (3/3) • To use an algorithm based on these simple rules we have to use metamodels that satisfy this requirements: • The root metaclass should not be connected to each other with any relationship except the composition relationship • Bidirectional metarelationships are not used • Composition metarelationship – traverse away from the composition • Generalization metarelationship – traverse down the inheritance tree • Root metaclass with a self-containing metarelationship – traverse away from the filled diamond until the current instance is the root

  14. 14/18 The developed traversal algorithm • Based on the previous design decisions we havedefined the following algorithm:

  15. 15/18 Example (1/2) • We demonstrate our approach on the finite state machine (FSM) modeling language (metamodel below)

  16. 16/18 Example (1/2) • According to our algorithm and the semantic specification, the following interpreter can be generated:

  17. 17/18 Conclusion • Identified the need for automatic generation of model-based tools • Proposed a semantics specification, which allows the generation of model interpreters • Consists of a semantics definition and a traversal algorithm • Showed a FSM example that uses our approach • This was our first step towards the theory of generating various model based tools from DSML definitions

  18. 18/18 Questions Contact me: tomaz.lukman@ijs.si

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