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Mining Metamodels From Instance Models: The MARS System

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... like models and source code conform to a schema, and are stored ... Repository artifacts might become obsolete if not transformed to conform to new schema. ... – PowerPoint PPT presentation

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Title: Mining Metamodels From Instance Models: The MARS System


1
Mining Metamodels From Instance Models The MARS
System
  • Faizan Javed
  • Department of Computer Information Sciences,
  • University of Alabama at Birmingham
  • The Fourth Annual Southeastern Software
    Engineering Conference (SE)2
  • 30th March 2005

2
Motivation
  • Software artifacts like models and source code
    conform to a schema, and are stored in a
    repository.
  • Evolution of schema might be required to address
    new feature requests.
  • Repository artifacts might become obsolete if not
    transformed to conform to new schema.
  • Example Java SDK new versions restructure or
    rename APIs.

3
Domain-Specific Modeling (DSM)
  • Raises level of abstraction, while narrowing
    design space to single domain of discourse.
  • Allows construction of models which follow domain
    abstractions and semantics allowing developers to
    work with domain concepts.
  • Metamodel Defines key elements of domain.
  • Models Defines specific configurations of the
    domain.

4
DSM modeling with GME
  • GME Generic Modeling Environment
  • Metamodel Networking

5
DSM Modeling with GME
  • Model CompanyA

6
Challenges of Mining Domain Instance Models
  • Metamodel drift inability to load models due to
    changes to metamodel.
  • Solution Infer metamodel from instance models !
  • Grammar Inference community has done extensive
    work on similar problem, albeit for programming
    language domain.

7
Challenges of Mining Domain Instance Models
  • Idea Apply grammar inference techniques to the
    metamodel inference problem.
  • Problem Modeling tools export XML files
    mismatch in representation expected by grammar
    inference techniques.
  • Solution Translate XML to textual DSL
    (Domain-Specific Language) !

8
Tools Used in the Project
  • GME Metamodel described with UML class diagrams,
    and constraints with OCL.
  • LISA An interactive environment where users can
    specify, generate, compile, and execute programs
    in a newly specified language.
  • DMS A program transformation system and
    re-engineering toolkit.

9
Overview of the MARS system
10
From GME models to MRL (Model Representation
Language)
XSLT
11
From MRL to Inferred Metamodel
LISADMS
12
Inferred vs. Original Metamodel
13
Limitations and Observations
  • Generalization hierarchy cant be inferred
    resulting in more elements in inferred metamodel.
  • Domain-Specific Visualization graphic assigned
    to metamodel entities cant be inferred.
  • OCL Constraints capture domain semantics that
    cant be captured with static diagrams. They are
    not explicitly indicated in domain models.

14
Related Work
  • The XTRACT System
  • 1) Infers DTD from XML documents
  • 2) Derives a regular expression for each element
    in the XML document.
  • 3) Uses the Minimum Description Length (MDL)
    principle to choose the best DTD from a set of
    candidate DTDs
  • ECFG Based System (Chidlovskii)
  • 1) Represents XML documents as structured
    examples of an unknown ECFG.
  • 2) Uses existing grammar inference techniques to
    infer the ECFG.

15
For more information
  • Project Website
  • http//www.cis.uab.edu/softcom/GenParse/mars.htm
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