Evaluation of UML-RT and Papyrus-RT for Modelling Self-Adaptive Systems

This paper is an evaluation of UML for Real-Time (UML-RT) for modelling Self-Adaptive Software (SAS) systems. Using a systematic review of the different features of UML-RT (optional capsules, SAP/SPP communication, hierarchical state machines, etc.), we analyse the suitability of the language for modelling structural and behavioural adaptations at design-and run-time. We evaluate these features in the context of their current state of support in Papyrus-RT, an Eclipse-based MDE tool for UML-RT recently developed by the Eclipse PolarSys Working Group. The use of UML-RT and Eclipse Papyrus for Real-Time (Papyrus-RT) for different kinds of adaptation is demonstrated using two real-time system case studies.

[1]  Jürgen Dingel,et al.  A survey of self-management in dynamic software architecture specifications , 2004, WOSS '04.

[2]  Rachid Guerraoui,et al.  Software-Based Replication for Fault Tolerance , 1997, Computer.

[3]  Holger Giese,et al.  A survey of approaches for the visual model-driven development of next generation software-intensive systems , 2006, J. Vis. Lang. Comput..

[4]  Christine Hofmeister Dynamic reconfiguration of distributed applications , 1993 .

[5]  James R. Cordy,et al.  Comparison and Evaluation of Model Transformation Tools , 2015 .

[6]  Bran Selic,et al.  Real-time object-oriented modeling , 1994, Wiley professional computing.

[7]  Jürgen Dingel,et al.  An executable formal semantics for UML-RT , 2014, Software & Systems Modeling.

[8]  Aniruddha S. Gokhale,et al.  Adaptive Failover for Real-Time Middleware with Passive Replication , 2009, 2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium.

[9]  Wilhelm Schäfer,et al.  Simulating Self-Adaptive Component-Based Systems Using MATLAB/Simulink , 2013, 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems.

[10]  Bernhard Rumpe,et al.  Model-driven Development of Complex Software : A Research Roadmap , 2007 .

[11]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[12]  Ernesto Posse PapyrusRT: Modelling and Code Generation (Invited Presentation) , 2015, OSS4MDE@MoDELS.

[13]  Thomas A. Henzinger Masaccio: A Formal Model for Embedded Components , 2000, IFIP TCS.

[14]  Mario Trapp,et al.  Runtime adaptation in safety-critical automotive systems , 2007 .

[15]  Ladan Tahvildari,et al.  Self-adaptive software: Landscape and research challenges , 2009, TAAS.

[16]  David Sinreich,et al.  An architectural blueprint for autonomic computing , 2006 .

[17]  Steffen Becker,et al.  The MechatronicUML method: model-driven software engineering of self-adaptive mechatronic systems , 2014, ICSE Companion.

[18]  Francis Bordeleau Model-Based Engineering: A New Era Based on Papyrus and Open Source Tooling , 2014, OSS4MDE@MoDELS.

[19]  Timothy Lethbridge,et al.  Promoting traits into model-driven development , 2017, Software & Systems Modeling.

[20]  Arnd Poetzsch-Heffter,et al.  Compositional Reasoning in Model-Based Verification of Adaptive Embedded Systems , 2008, 2008 Sixth IEEE International Conference on Software Engineering and Formal Methods.

[21]  Alexander Pretschner,et al.  Approaching a Discrete-Continuous UML: Tool Support and Formalization , 2001, pUML.

[22]  Mary Shaw,et al.  Software Engineering for Self-Adaptive Systems: A Research Roadmap , 2009, Software Engineering for Self-Adaptive Systems.

[23]  Bran Selic,et al.  Using UML for Modeling Complex Real-Time Systems , 1998, LCTES.

[24]  David Harel,et al.  Statecharts: A Visual Formalism for Complex Systems , 1987, Sci. Comput. Program..

[25]  Bran Selic Accounting for platform effects in the design of real-time software using model-based methods , 2008, IBM Syst. J..

[26]  Vijay Kumar,et al.  Hierarchical Hybrid Modeling of Embedded Systems , 2001, EMSOFT.