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A Conceptual Generic Framework to Debugging in the Domain-Specific Modeling Languages for Multi-Agent Systems

Authors Baris Tekin Tezel , Geylani Kardas

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Baris Tekin Tezel
  • Department of Computer Science, Dokuz Eylul University, Izmir, Turkey
  • International Computer Institute, Ege University, Izmir, Turkey
Geylani Kardas
  • International Computer Institute, Ege University, Izmir, Turkey

Funding

  • Tezel, Baris Tekin: The first author would like to thank TUBITAK-BIDEB for financial support during his PhD studies.

Cite AsGet BibTex

Baris Tekin Tezel and Geylani Kardas. A Conceptual Generic Framework to Debugging in the Domain-Specific Modeling Languages for Multi-Agent Systems. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 8:1-8:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/OASIcs.SLATE.2019.8

Abstract

Despite the existence of many agent programming environments and platforms, the developers may still encounter difficulties on implementing Multi-agent Systems (MASs) due to the complexity of agent features and agent interactions inside the MAS organizations. Working in a higher abstraction layer and modeling agent components within a model-driven engineering (MDE) process before going into depths of MAS implementation may facilitate MAS development. Perhaps the most popular way of applying MDE for MAS is based on creating Domain-specific Modeling Languages (DSMLs) with including appropriate integrated development environments (IDEs) in which both modeling and code generation for system-to-be-developed can be performed properly. Although IDEs of these MAS DSMLs provide some sort of checks on modeled systems according to the related DSML’s syntax and semantics descriptions, currently they do not have a built-in support for debugging these MAS models. That deficiency causes the agent developers not to be sure on the correctness of the prepared MAS model at the design phase. To help filling this gap, we introduce a conceptual generic debugging framework supporting the design of agent components inside the modeling environments of MAS DSMLs. The debugging framework is composed of 4 different metamodels and a simulator. Use of the proposed framework starts with modeling a MAS using a design language and transforming design model instances to a run-time model. According to the framework, the run-time model is simulated on a built-in simulator for debugging. The framework also provides a control mechanism for the simulation in the form of a simulation environment model.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Domain specific languages
  • Software and its engineering → Software testing and debugging
  • Computing methodologies → Multi-agent systems
  • Computing methodologies → Modeling and simulation
Keywords
  • debugging
  • domain-specific modeling languages
  • multi-agent systems
  • simulation

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References

  1. Fabio Luigi Bellifemine, Giovanni Caire, and Dominic Greenwood. Developing multi-agent systems with JADE. John Wiley &Sons, 3 edition, 2007. Google Scholar
  2. Federico Bergenti, Eleonora Iotti, Stefania Monica, and Agostino Poggi. Agent-oriented model-driven development for JADE with the JADEL programming language. Computer Languages, Systems & Structures, 50:142-158, 2017. Google Scholar
  3. Ghassan Beydoun, Graham Low, Brian Henderson-Sellers, Haralambos Mouratidis, Jorge J Gomez-Sanz, Juan Pavon, and Cesar Gonzalez-Perez. FAML: A Generic Metamodel for MAS Development. IEEE Transactions on Software Engineering, 35(6):841-863, 2009. Google Scholar
  4. Andreas Blunk, Joachim Fischer, and Daniel A. Sadilek. Modelling a Debugger for an Imperative Voice Control Language. In SDL 2009: Design for Motes and Mobiles. SDL 2009. Lecture Notes in Computer Science, volume 5719, pages 149-164. Springer, 2009. Google Scholar
  5. Erwan Bousse, Jonathan Corley, Benoit Combemale, Jeff Gray, and Benoit Baudry. Supporting efficient and advanced omniscient debugging for xDSMLs. In Proceedings of the 2015 ACM SIGPLAN Int. Conf. Software Language Engineering (SLE 2015), pages 137-148, 2015. Google Scholar
  6. Erwan Bousse, Dorian Leroy, Benoit Combemale, Manuel Wimmer, and Benoit Baudry. Omniscient debugging for executable DSLs. Journal of Systems and Software, 137:261-288, 2018. Google Scholar
  7. Moharram Challenger, Sebla Demirkol, Sinem Getir, Marjan Mernik, Geylani Kardas, and Tomaz Kosar. On the use of a domain-specific modeling language in the development of multiagent systems. Engineering Applications of Artificial Intelligence, 28:111-141, 2014. Google Scholar
  8. Moharram Challenger, Marjan Mernik, Geylani Kardas, and Tomaž Kosar. Declarative specifications for the development of multi-agent systems. Computer Standards &Interfaces, 43:91-115, 2016. Google Scholar
  9. Andrei Chiş, Marcus Denker, Tudor Gîrba, and Oscar Nierstrasz. Practical domain-specific debuggers using the Moldable Debugger framework. Computer Languages, Systems & Structures, 44(Part A):89-113, 2016. Google Scholar
  10. Rem Collier. Debugging agents in agent factory. In International Workshop on Programming Multi-Agent Systems, pages 229-248. Springer, 2006. Google Scholar
  11. Mehdi Dastani, Jaap Brandsema, Amco Dubel, and John-Jules Ch Meyer. Debugging BDI-based multi-agent programs. In International workshop on programming multi-agent systems, pages 151-169. Springer, 2009. Google Scholar
  12. Joao Faccin and Ingrid Nunes. A tool-supported development method for improved BDI plan selection. Engineering Applications of Artificial Intelligence, 62:195-213, 2017. Google Scholar
  13. Josep Silva Galiana. The New Generation of Algorithmic Debuggers. In 1st Symposium on Languages, Applications and Technologies (SLATE 2012), page 3, 2012. Google Scholar
  14. Enyo José Tavares Gonçalves, Mariela I Cortés, Gustavo Augusto Lima Campos, Yrleyjander S Lopes, Emmanuel SS Freire, Viviane Torres da Silva, Kleinner Silva Farias de Oliveira, and Marcos Antonio de Oliveira. MAS-ML 2.0: Supporting the modelling of multi-agent systems with different agent architectures. Journal of Systems and Software, 108:77-109, 2015. Google Scholar
  15. Christian Hahn. A Domain Specific Modeling Language for Multiagent Systems. In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1, pages 233-240, Estoril, Portugal, 2008. International Foundation for Autonomous Agents and Multiagent Systems. AAMAS '08. URL: http://dl.acm.org/citation.cfm?id=1402383.1402420.
  16. Christian Hahn, Cristian Madrigal-Mora, and Klaus Fischer. A platform-independent metamodel for multiagent systems. Autonomous Agents and Multi-Agent Systems, 18(2):239-266, 2009. Google Scholar
  17. Brent Hailpern and Padmanabhan Santhanam. Software debugging, testing, and verification. IBM Systems Journal, 41(1):4-12, 2002. Google Scholar
  18. Ábel Hegedüs, István Ráth, and Dániel Varró. Replaying execution trace models for dynamic modeling languages. Periodica Polytechnica Electrical Engineering and Computer Science, 56(3):71-82, 2012. Google Scholar
  19. Koen V Hindriks. Programming rational agents in GOAL. In Multi-agent programming: languages and tools and applications, pages 119-157. Springer, New York, 2009. Google Scholar
  20. Koen V Hindriks. Debugging is explaining. In International Conference on Principles and Practice of Multi-Agent Systems, pages 31-45. Springer, 2012. Google Scholar
  21. Nick Howden, Ralph Rönnquist, Andrew Hodgson, and Andrew Lucas. JACK intelligent agents-summary of an agent infrastructure. In 5th International conference on autonomous agents, 2001. Google Scholar
  22. Jomi F Hübner, Olivier Boissier, Rosine Kitio, and Alessandro Ricci. Instrumenting multi-agent organisations with organisational artifacts and agents. Autonomous agents and multi-agent systems, 20(3):369-400, 2010. Google Scholar
  23. Geylani Kardas. Model-driven development of multiagent systems: a survey and evaluation. The Knowledge Engineering Review, 28(04):479-503, 2013. Google Scholar
  24. Geylani Kardas, Emine Bircan, and Moharram Challenger. Supporting the platform extensibility for the model-driven development of agent systems by the interoperability between domain-specific modeling languages of multi-agent systems. Comput Sci Inf Syst, 14(3):875-912, 2017. Google Scholar
  25. Geylani Kardas and Jorge J. Gomez-Sanz. Special issue on model-driven engineering of multi-agent systems in theory and practice. Computer Languages, Systems & Structures, 50:140-141, 2017. Google Scholar
  26. Geylani Kardas, Baris Tekin Tezel, and Moharram Challenger. Domain-specific modelling language for belief-desire-intention software agents. IET Software, 12(4):356-364, 2018. Google Scholar
  27. Tomaž Kosar, Marjan Mernik, Jeff Gray, and Tomaž Kos. Debugging measurement systems using a domain-specific modeling language. Computers in Industry, 65(4):622-635, May 2014. URL: http://dx.doi.org/10.1016/j.compind.2014.01.013.
  28. Ricky T Lindeman, Lennart C L Kats, and Eelco Visser. Declaratively Defining Domain-Specific Language Debuggers. In International Conference on Generative Programming and Component Engineering (GPCE), pages 127-136, 2012. URL: http://dx.doi.org/10.1145/2189751.2047885.
  29. Raphael Mannadiar and Hans Vangheluwe. Debugging in Domain-Specific Modelling. In Lecture Notes in Computer Science, volume 6563, pages 276-285. Springer, 2011. Google Scholar
  30. Bart Meyers, Romuald Deshayes, Levi Lucio, Eugene Syriani, Hans Vangheluwe, and Manuel Wimmer. ProMoBox: a framework for generating domain-specific property languages. In International Conference on Software Language Engineering, pages 1-20. Springer, 2014. Google Scholar
  31. Divine T Ndumu, Hyacinth S Nwana, Lyndon C Lee, and Jaron C Collis. Visualising and debugging distributed multi-agent systems. In Proceedings of the third annual conference on Autonomous Agents - AGENTS '99, pages 326-333, New York, New York, USA, 1999. ACM Press. URL: http://dx.doi.org/10.1145/301136.301220.
  32. Hyacinth S. Nwana, Divine T. Ndumu, Lyndon C. Lee, and Jaron C. Collis. Zeus: A toolkit for building distributed multiagent systems. Applied Artificial Intelligence, 13(1-2):129-185, January 1999. URL: http://dx.doi.org/10.1080/088395199117513.
  33. Alexander Pokahr, Lars Braubach, Andrzej Walczak, and Winfried Lamersdorf. Jadex-engineering goal-oriented agents. Developing multi-agent systems with JADE, pages 254-258, 2007. Google Scholar
  34. David Poutakidis, Lin Padgham, and Michael Winikoff. Debugging multi-agent systems using design artifacts: The case of interaction protocols. In Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2, pages 960-967. ACM, 2002. Google Scholar
  35. Amal El Fallah Seghrouchni and Alexandru Suna. Claim and sympa: A programming environment for intelligent and mobile agents. In Multi-Agent Programming, pages 95-122. Springer, 2005. Google Scholar
  36. Onn Shehory and Arnon Sturm. Agent-Oriented Software Engineering: Reflections on Architectures, Methodologies, Languages, and Frameworks. Springer-Verlag Berlin Heidelberg, 2014. Google Scholar
  37. Josep Silva. A survey on algorithmic debugging strategies. Advances in engineering software, 42(11):976-991, 2011. Google Scholar
  38. Josep Silva. A vocabulary of program slicing-based techniques. ACM computing surveys (CSUR), 44(3):12, 2012. Google Scholar
  39. Reid G. Smith. The contract net protocol: High-level communication and control in a distributed problem solver. EEE Transactions on computers, 12:1104-1113, 1980. Google Scholar
  40. Baris T. Tezel, Moharram Challenger, and Geylani Kardas. A metamodel for Jason BDI agents. In 5th Symposium on Languages, Applications and Technologies (SLATE'16), volume 51, pages 8:1 - -8:9, 2016. Google Scholar
  41. Baris Tekin Tezel and Geylani Kardas. Towards Providing Debugging in the Domain-Specific Modeling Languages for Software Agents. In Proceedings of the Second International Workshop on Debugging in Model-Driven Engineering (MDEbug 2018) co-located with ACM/IEEE 21st International Conference on Model Driven Engineering Languages and Systems (MODELS 2018), 2018. Google Scholar
  42. Marc H Van Liedekerke and Nicholas M Avouris. Debugging multi-agent systems. Information and Software Technology, 37(2):103-112, 1995. Google Scholar
  43. Simon Van Mierlo. A multi-paradigm modelling approach for engineering model debugging environments. PhD thesis, University of Antwerp, 2018. Google Scholar
  44. Michael Wooldridge. An introduction to multiagent systems. John Wiley &Sons, 2009. Google Scholar
  45. Hui Wu, Jeff Gray, and Marjan Mernik. Grammar-driven generation of domain-specific language debuggers. Software: Practice and Experience, 38(10):1073-1103, 2008. Google Scholar
  46. Andreas Zeller. Why Programs Fail: A Guide to Systematic Debugging. Morgan Kaufmann, 2009. Google Scholar
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