Towards generic modularization transformations

Modularization concepts have been introduced in several modeling languages in order to tackle the problem that real-world models quickly become large monolithic artifacts. Having these concepts at hand allows for structuring models during modeling activities. However, legacy models often lack a proper structure, and thus, still remain monolithic artifacts. In order to tackle this problem, we present in this paper a modularization transformation which can be reused for several modeling languages by binding their concrete concepts to the generic ones offered by the modularization transformation. This binding is enough to reuse different modularization strategies provided by search-based model transformations. We demonstrate the applicability of the modularization approach for Ecore models.

[1]  Kalyanmoy Deb,et al.  An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.

[2]  Adnan Shaout,et al.  Many-Objective Software Remodularization Using NSGA-III , 2015, TSEM.

[3]  Gerti Kappel,et al.  A survey on UML-based aspect-oriented design modeling , 2011, CSUR.

[4]  Kalyanmoy Deb,et al.  Towards a Quick Computation of Well-Spread Pareto-Optimal Solutions , 2003, EMO.

[5]  T. S. E. Maibaum,et al.  A Query Structured Approach for Model Transformation , 2014, AMT@MoDELS.

[6]  Uwe Aßmann,et al.  Role-based generic model refactoring , 2010, MODELS'10.

[7]  Hartmut Schmeck,et al.  Theory and Algorithms for Finding Knees , 2013, EMO.

[8]  Jean-Philippe Diguet,et al.  Extensible Global Model Management with Meta-model Subsets and Model Synchronization , 2014, GEMOC@MoDELS.

[9]  Kalyanmoy Deb,et al.  Finding Knees in Multi-objective Optimization , 2004, PPSN.

[10]  Jordi Cabot,et al.  Model-Driven Software Engineering in Practice , 2017, Synthesis Lectures on Software Engineering.

[11]  Gabriele Taentzer,et al.  Henshin: advanced concepts and tools for in-place EMF model transformations , 2010, MODELS'10.

[12]  Xin Yao,et al.  Software Module Clustering as a Multi-Objective Search Problem , 2011, IEEE Transactions on Software Engineering.

[13]  Juan de Lara,et al.  EMF Splitter: A Structured Approach to EMF Modularity , 2014, XM@MoDELS.

[14]  Uwe Aßmann,et al.  Reuseware - Adding Modularity to Your Language of Choice , 2007, J. Object Technol..

[15]  Juan de Lara,et al.  Generic Model Transformations: Write Once, Reuse Everywhere , 2011, ICMT@TOOLS.

[16]  Jörg Kienzle,et al.  Concern-Oriented Software Design , 2013, MoDELS.

[17]  Werner Retschitzegger,et al.  Reusing Model Transformations across Heterogeneous Metamodels , 2012, Electron. Commun. Eur. Assoc. Softw. Sci. Technol..

[18]  Gerti Kappel,et al.  Reality Check for Model Transformation Reuse: The ATL Transformation Zoo Case Study , 2013, AMT@MoDELS.

[19]  Marsha Chechik,et al.  Splitting Models Using Information Retrieval and Model Crawling Techniques , 2014, FASE.

[20]  Juan de Lara,et al.  Fragmenta: A theory of fragmentation for MDE , 2015, 2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS).

[21]  Mark Harman,et al.  The Current State and Future of Search Based Software Engineering , 2007, Future of Software Engineering (FOSE '07).

[22]  Gabriele Taentzer,et al.  Tool support for clustering large meta-models , 2013, BigMDE '13.

[23]  Doreen Meier,et al.  Structured Design Fundamentals Of A Discipline Of Computer Program And Systems Design , 2016 .

[24]  Colin Atkinson,et al.  Supporting View-Based Development through Orthographic Software Modeling , 2009, ENASE.

[25]  J. Troya,et al.  Marrying Search-based Optimization and Model Transformation Technology , 2015 .

[26]  WimmerManuel,et al.  A survey on UML-based aspect-oriented design modeling , 2011 .

[27]  Jan Mendling,et al.  Modularity in Process Models: Review and Effects , 2008, BPM.

[28]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..