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Validation of reasoning engines an adaptation mechanisms for self-adaptive systems

Freddy Munoz 1
1 TRISKELL - Reliable and efficient component based software engineering
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Self-adaptive system are software systems capable of sensing their working environment (through sensors), reason and make decisions on how to adapt facing environmental changes (through a reasoning engine), and reconfigure their internal structure in order apply adaptations (through an adaptation mechanism). These systems can provide effective assistance in a large number of human activities. Yet, they will fully deliver their promises only if system engineers can ensure that decisions and adaptations are correct on all situations. This requires robust techniques for validating that the reasoning process and adaptation mechanisms implemented in such systems are correct. In this thesis I address the validation of reasoning engines and adaptation mechanism base on aspect-oriented programming. Reasoning engines are pieces of software entitled of reasoning on a large number of factors in order to decide how to adapt given an environmental change. Ensuring that the decisions of these engines are correct for every possible environment change is critical. Wrong decision will lead to faulty adaptation that may prevent the system to work properly. Yet, validating that reasoning engines make the right decision is challenging because of the large number of possible environmental changes. In this thesis I introduce multi-dimensional covering arrays (MDCA) for sampling the environmental conditions that mat affect the decision making process. MDCA specifically targets environments that can trigger complex decision by explicitly integrating the notion of history in the environment sample. Aspect oriented programming (AOP) provide the means to developers to augment or replace the system structure or behavior, properties that make AOP a good adaptation mechanism. Yet, when using AOP it is difficult to (i) foresee interactions between different aspects and the base system, (ii) control the places that aspects will advise and invade, (iii) ensure that aspects will perform safely on evolution (aspects or the base system). These difficulties hamper the validation and adoption of AOP in general. In this thesis I introduce an interactions specification framework (ABIS), which allows developers to control the aspects interactions with the base system by specifying the places that aspects are allowed to advice. ABIS enables developers to reduce the time needed to diagnose and correct problems due to faulty aspects.
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Submitted on : Tuesday, November 23, 2010 - 11:19:01 AM
Last modification on : Friday, November 16, 2018 - 1:30:34 AM
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  • HAL Id : tel-00538565, version 1


Freddy Munoz. Validation of reasoning engines an adaptation mechanisms for self-adaptive systems. Software Engineering [cs.SE]. Université Rennes 1, 2010. English. ⟨tel-00538565⟩



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