102,202 research outputs found

    Modelling and analyzing adaptive self-assembling strategies with Maude

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    Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify and analyse a prominent example of adaptive system: robot swarms equipped with obstacle-avoidance self-assembly strategies. The analysis exploits the statistical model checker PVesta

    A study of systems implementation languages for the POCCNET system

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    The results are presented of a study of systems implementation languages for the Payload Operations Control Center Network (POCCNET). Criteria are developed for evaluating the languages, and fifteen existing languages are evaluated on the basis of these criteria

    Proceedings of International Workshop "Global Computing: Programming Environments, Languages, Security and Analysis of Systems"

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    According to the IST/ FET proactive initiative on GLOBAL COMPUTING, the goal is to obtain techniques (models, frameworks, methods, algorithms) for constructing systems that are flexible, dependable, secure, robust and efficient. The dominant concerns are not those of representing and manipulating data efficiently but rather those of handling the co-ordination and interaction, security, reliability, robustness, failure modes, and control of risk of the entities in the system and the overall design, description and performance of the system itself. Completely different paradigms of computer science may have to be developed to tackle these issues effectively. The research should concentrate on systems having the following characteristics: • The systems are composed of autonomous computational entities where activity is not centrally controlled, either because global control is impossible or impractical, or because the entities are created or controlled by different owners. • The computational entities are mobile, due to the movement of the physical platforms or by movement of the entity from one platform to another. • The configuration varies over time. For instance, the system is open to the introduction of new computational entities and likewise their deletion. The behaviour of the entities may vary over time. • The systems operate with incomplete information about the environment. For instance, information becomes rapidly out of date and mobility requires information about the environment to be discovered. The ultimate goal of the research action is to provide a solid scientific foundation for the design of such systems, and to lay the groundwork for achieving effective principles for building and analysing such systems. This workshop covers the aspects related to languages and programming environments as well as analysis of systems and resources involving 9 projects (AGILE , DART, DEGAS , MIKADO, MRG, MYTHS, PEPITO, PROFUNDIS, SECURE) out of the 13 founded under the initiative. After an year from the start of the projects, the goal of the workshop is to fix the state of the art on the topics covered by the two clusters related to programming environments and analysis of systems as well as to devise strategies and new ideas to profitably continue the research effort towards the overall objective of the initiative. We acknowledge the Dipartimento di Informatica and Tlc of the University of Trento, the Comune di Rovereto, the project DEGAS for partially funding the event and the Events and Meetings Office of the University of Trento for the valuable collaboration

    Robust Watermarking using Hidden Markov Models

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    Software piracy is the unauthorized copying or distribution of software. It is a growing problem that results in annual losses in the billions of dollars. Prevention is a difficult problem since digital documents are easy to copy and distribute. Watermarking is a possible defense against software piracy. A software watermark consists of information embedded in the software, which allows it to be identified. A watermark can act as a deterrent to unauthorized copying, since it can be used to provide evidence for legal action against those responsible for piracy.In this project, we present a novel software watermarking scheme that is inspired by the success of previous research focused on detecting metamorphic viruses. We use a trained hidden Markov model (HMM) to detect a specific copy of software. We give experimental results that show our scheme is robust. That is, we can identify the original software even after it has been extensively modified, as might occur as part of an attack on the watermarking scheme
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