This research is supported by NSF CAREER award CCF-1052616 MT-Scribe: A Flexible Tool to Support Model Evolution Yu SunUniversity of Alabama at Birmingham.

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Presentation transcript:

This research is supported by NSF CAREER award CCF MT-Scribe: A Flexible Tool to Support Model Evolution Yu SunUniversity of Alabama at Birmingham Jeff GrayUniversity of Alabama Jules WhiteVirginia Tech SPLASH2010 Reno, Nevada, USA October 18 th, 2010

Manual Transformation is Challenging  Manually editing is the most direct way to transform models  Manual editing is  Tedious  Time-consuming  Error-prone 2

Using Model Transformation Languages  MTLs are specialized languages to implement model transformation tasks  Automate scaling up models by programming 3 QVT Query/View/Transformation ECL Embedded Constrain Language GReAT Graph Rewriting and Transformation Popular Model Transformation Languages Challenge 1: Steep learning curve Challenge 2: Deep understanding about the domain definitions

Solution: Model Transformation By Demonstration  A complete model transformation framework  Specify and execute model transformations  Users are fully isolated from MTLs and domain definitions  Infer and generate model transformation patterns by demonstrating model transformations on concrete examples 4 Add, Remove, Update

Overview of MT-Scribe

A B cde B cde F B cde MT-Scribe to Support Model Evolution 6

Thank You  Questions and Comments?  Additional questions  Model Transformation By Demonstration This research is supported by NSF CAREER award CCF