Verification of lack of emergent behavior in extending a social network of agents

The scalability of the system is of vital importance in the design of social networks. This research attempts to establish a comprehensive framework for analysis and validation of requirements and design documents for software systems. In previous work, we applied this framework to analyze the requirements of a social network of agents with respect to scalability of the system. In our approach, system requirements were expressed using scenario-based specifications. Scenarios are appealing because of their expressive power and simplicity. Moreover, due to the clear and concise notation of scenarios, they can be used to analyze the system requirements for general validity, lack of deadlock, and existence of emergent behavior. In this paper a methodology is presented to formally verify that certain scenarios do not emerge in the system’s behavior. This methodology is devised to indicate whether or not the new requirements of the system are consistent with the current requirements in place. A larger prototype of a social network of MSA for semantic search is utilized to illustrate the developed methodology.

[1]  Jeff Magee,et al.  Negative scenarios for implied scenario elicitation , 2002, FSE 2002.

[2]  David Harel,et al.  Synthesizing State-Based Object Systems from LSC Specifications , 2000, Int. J. Found. Comput. Sci..

[3]  Behrouz Homayoun Far,et al.  An automated ontology generation technique for an emergent behavior detection system , 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

[4]  Eric Moulines,et al.  Inference in hidden Markov models , 2010, Springer series in statistics.

[5]  Erkki Mäkinen,et al.  MAS — an interactive synthesizer to support behavioral modelling in UML , 2001, ICSE.

[6]  N. Lin,et al.  Social Resources and Strength of Ties: Structural Factors in Occupational Status Attainment , 1981, Social Capital, Social Support and Stratification.

[7]  Behrouz Homayoun Far,et al.  Eliciting Scenarios from Scenarios , 2008, SEKE.

[8]  T. Systa,et al.  MAS - an interactive synthesizer to support behavioral modeling in UML , 2001, Proceedings of the 23rd International Conference on Software Engineering. ICSE 2001.

[9]  Johann Schumann,et al.  Generating statechart designs from scenarios , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.

[10]  Henry Muccini,et al.  Detecting Implied Scenarios Analyzing Non-local Branching Choices , 2003, FASE.

[11]  Pablo Rodriguez,et al.  The little engine(s) that could: scaling online social networks , 2010, SIGCOMM '10.

[12]  Rajeev Alur,et al.  Inference of message sequence charts , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.

[13]  Mohsen Afsharchi,et al.  Realization of Semantic Search Using Concept Learning and Document Annotation Agents , 2009, SEKE.

[14]  Behrouz Homayoun Far,et al.  Calculating the strength of ties of a social network in a semantic search system using hidden Markov models , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[15]  Diane L. Gibson,et al.  Demonstrating the Impact and Benefits of CMMI ® : An Update and Preliminary Results , 2003 .

[16]  Pablo Rodriguez,et al.  The little engine(s) that could: scaling online social networks , 2012, TNET.

[17]  Sebastián Uchitel,et al.  Synthesis of Behavioral Models from Scenarios , 2003, IEEE Trans. Software Eng..

[18]  Tamás Nepusz,et al.  Measuring tie-strength in virtual social networks , 2006 .

[19]  Eric Gilbert,et al.  Predicting tie strength with social media , 2009, CHI.

[20]  Behrouz Homayoun Far,et al.  A Technique and a Tool to Detect Emergent Behavior of Distributed Systems Using Scenario-Based Specifications , 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

[21]  Leo Obrst,et al.  The Semantic Web: A Guide to the Future of XML, Web Services and Knowledge Management , 2003 .

[22]  Behrouz Homayoun Far,et al.  Automated Construction of System Domain Knowledge Using an Ontology-Based Approach (S) , 2013, SEKE.

[23]  Behrouz Homayoun Far,et al.  Analyzing the scalability of a social network of agents , 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

[24]  Mark S. Granovetter.  T H E S T R E N G T H O F WEAK TIES: A NETWORK THEORY REVISITED , 1983 .

[25]  Manfred Broy,et al.  From MSCs to Statecharts , 1998, DIPES.

[26]  Christopher A. Rouff,et al.  Agent Technology from a Formal Perspective , 2006 .

[27]  Behrouz Homayoun Far,et al.  Detecting Emergent Behavior in Distributed Systems using Scenario-Based Specifications , 2012, Int. J. Softw. Eng. Knowl. Eng..

[28]  Madhavan Mukund,et al.  Causal Closure for MSC Languages , 2005, FSTTCS.

[29]  Peter Triantafillou,et al.  eXO: Decentralized Autonomous Scalable Social Networking , 2011, CIDR.

[30]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[31]  Steven B. Andrews,et al.  Structural Holes: The Social Structure of Competition , 1995, The SAGE Encyclopedia of Research Design.

[32]  Behrouz Homayoun Far,et al.  Detecting Emergent Behavior in a Social Network of Agents , 2013, The Influence of Technology on Social Network Analysis and Mining.

[33]  Johann Schumann,et al.  Scenario-Based Engineering of Multi-Agent Systems , 2006 .