10 research outputs found

    Game theoretic modeling and analysis : A co-evolutionary, agent-based approach

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    Ph.DDOCTOR OF PHILOSOPH

    Model based test suite minimization using metaheuristics

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    Software testing is one of the most widely used methods for quality assurance and fault detection purposes. However, it is one of the most expensive, tedious and time consuming activities in software development life cycle. Code-based and specification-based testing has been going on for almost four decades. Model-based testing (MBT) is a relatively new approach to software testing where the software models as opposed to other artifacts (i.e. source code) are used as primary source of test cases. Models are simplified representation of a software system and are cheaper to execute than the original or deployed system. The main objective of the research presented in this thesis is the development of a framework for improving the efficiency and effectiveness of test suites generated from UML models. It focuses on three activities: transformation of Activity Diagram (AD) model into Colored Petri Net (CPN) model, generation and evaluation of AD based test suite and optimization of AD based test suite. Unified Modeling Language (UML) is a de facto standard for software system analysis and design. UML models can be categorized into structural and behavioral models. AD is a behavioral type of UML model and since major revision in UML version 2.x it has a new Petri Nets like semantics. It has wide application scope including embedded, workflow and web-service systems. For this reason this thesis concentrates on AD models. Informal semantics of UML generally and AD specially is a major challenge in the development of UML based verification and validation tools. One solution to this challenge is transforming a UML model into an executable formal model. In the thesis, a three step transformation methodology is proposed for resolving ambiguities in an AD model and then transforming it into a CPN representation which is a well known formal language with extensive tool support. Test case generation is one of the most critical and labor intensive activities in testing processes. The flow oriented semantic of AD suits modeling both sequential and concurrent systems. The thesis presented a novel technique to generate test cases from AD using a stochastic algorithm. In order to determine if the generated test suite is adequate, two test suite adequacy analysis techniques based on structural coverage and mutation have been proposed. In terms of structural coverage, two separate coverage criteria are also proposed to evaluate the adequacy of the test suite from both perspectives, sequential and concurrent. Mutation analysis is a fault-based technique to determine if the test suite is adequate for detecting particular types of faults. Four categories of mutation operators are defined to seed specific faults into the mutant model. Another focus of thesis is to improve the test suite efficiency without compromising its effectiveness. One way of achieving this is identifying and removing the redundant test cases. It has been shown that the test suite minimization by removing redundant test cases is a combinatorial optimization problem. An evolutionary computation based test suite minimization technique is developed to address the test suite minimization problem and its performance is empirically compared with other well known heuristic algorithms. Additionally, statistical analysis is performed to characterize the fitness landscape of test suite minimization problems. The proposed test suite minimization solution is extended to include multi-objective minimization. As the redundancy is contextual, different criteria and their combination can significantly change the solution test suite. Therefore, the last part of the thesis describes an investigation into multi-objective test suite minimization and optimization algorithms. The proposed framework is demonstrated and evaluated using prototype tools and case study models. Empirical results have shown that the techniques developed within the framework are effective in model based test suite generation and optimizatio

    Task Allocation in Foraging Robot Swarms:The Role of Information Sharing

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    Autonomous task allocation is a desirable feature of robot swarms that collect and deliver items in scenarios where congestion, caused by accumulated items or robots, can temporarily interfere with swarm behaviour. In such settings, self-regulation of workforce can prevent unnecessary energy consumption. We explore two types of self-regulation: non-social, where robots become idle upon experiencing congestion, and social, where robots broadcast information about congestion to their team mates in order to socially inhibit foraging. We show that while both types of self-regulation can lead to improved energy efficiency and increase the amount of resource collected, the speed with which information about congestion flows through a swarm affects the scalability of these algorithms

    Using MapReduce Streaming for Distributed Life Simulation on the Cloud

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    Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

    Living in a natural world

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    Die Dissertation besteht aus drei Teilen: der erste behandelt Rationalität und deren Bedeutung für alle Fragen des Lebens, nicht nur für einen reduzierten – für wissenschaftliche Untersuchungen reservierten – Teilbereich der Welt; der zweite Teil ist metaphysischer Natur und skizziert den postulierten Aufbau der Welt anhand der im ersten Teil erläuterten Prinzipien. Im dritten Teil frage ich – und gebe vorläufige Antworten – wie die Ergebnisse der vorherigen Teile unseren Blickwinkel auf empfindsame Wesen des Universums – darunter Menschen – ändern. Nur wenn wir rational sind können wir das Maximum an Information aus unserer Umwelt extrahieren. Unser beste Weg zum Erkenntnisgewinn sollte auch Leitfaden für unsere Spiritualität, Ethik, unsere Ansichten über den Sinn des Lebens etc sein. Es ist wichtig die sich mit unserem Erkenntnisstand ändernden Standards der Rationalität auf alle menschlichen Unterfangen anzuwenden. Für Individuen bedeutet Wissen gute mentale Modelle der Welt zu besitzen: je genauer effektive Faktoren in der Welt gespiegelt werden, umso besser können angestrebte Ziele erreicht werden. Unwissenheit führt zu Inaktivität und Passivität. Die Bewährungsprobe für Wissen und Philosophie ist die: werden durch sie die Art und Weise wie wir die Welt, unser Leben, und – letztlich am Wichtigsten – die Art und Weise wie wir handeln, verändert?The thesis consists of three parts: the first being on rationality and its import in tackling all questions facing us in our lives, not only a reduced domain of scientific investigation; the second, metaphysical in nature, forming an essay on the nature of the world, especially as informed by the principles of rationality sketched in the previous part; and the third, applying the findings of the previous sections to sentient agents – among them humans – in this universe. I argue that the rational approach is the best way to approach all questions facing us in our lives. Only by being rational can we extract as much information from our environment as possible. Our best way of gaining knowledge should quite naturally also influence our spirituality, our ethics, our view of the meaning of life and so on. It is important to apply the open standards of rationality to all areas of interest to humans. The agent centric approach is central to the thesis. For individuals, knowledge means having a good mental model of the world: the closer to the actual effective factors in the world, the more potential there is for action leading to achievement of goals. Ignorance condemns one to inaction and passivity. The litmus test for knowledge – and philosophy – is this: does it change the way we view the world, our life, and, ultimately and most importantly, the way we act

    Advances in Computational Social Science and Social Simulation

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    Aquesta conferència és la celebració conjunta de la "10th Artificial Economics Conference AE", la "10th Conference of the European Social Simulation Association ESSA" i la "1st Simulating the Past to Understand Human History SPUHH".Conferència organitzada pel Laboratory for Socio­-Historical Dynamics Simulation (LSDS-­UAB) de la Universitat Autònoma de Barcelona.Readers will find results of recent research on computational social science and social simulation economics, management, sociology,and history written by leading experts in the field. SOCIAL SIMULATION (former ESSA) conferences constitute annual events which serve as an international platform for the exchange of ideas and discussion of cutting edge research in the field of social simulations, both from the theoretical as well as applied perspective, and the 2014 edition benefits from the cross-fertilization of three different research communities into one single event. The volume consists of 122 articles, corresponding to most of the contributions to the conferences, in three different formats: short abstracts (presentation of work-in-progress research), posters (presentation of models and results), and full papers (presentation of social simulation research including results and discussion). The compilation is completed with indexing lists to help finding articles by title, author and thematic content. We are convinced that this book will serve interested readers as a useful compendium which presents in a nutshell the most recent advances at the frontiers of computational social sciences and social simulation researc
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