Submitted by Aelson Maciera (aelsoncm@terra.com.br) on 2017-04-17T18:58:23Z No. of bitstreams: 1 DissMAS.pdf: 4063634 bytes, checksum: deabb30ec4d63266b4b9dc58fe79287a (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-04-20T12:22:31Z (GMT) No. of bitstreams: 1 DissMAS.pdf: 4063634 bytes, checksum: deabb30ec4d63266b4b9dc58fe79287a (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-04-20T12:22:39Z (GMT) No. of bitstreams: 1 DissMAS.pdf: 4063634 bytes, checksum: deabb30ec4d63266b4b9dc58fe79287a (MD5) / Made available in DSpace on 2017-04-20T12:26:34Z (GMT). No. of bitstreams: 1 DissMAS.pdf: 4063634 bytes, checksum: deabb30ec4d63266b4b9dc58fe79287a (MD5) Previous issue date: 2016-08-19 / Não recebi financiamento / Adaptive systems are able to adapt themselves according to changes in its execution environment or the user's needs. Monitors are essential for the development of such systems because they are responsible for collecting and pre-processing the context data. By a search in systems found in repositories and literature, it was observed that monitors are sometimes designed and implemented in an inappropriate way, exhibiting the following characteristics: i) they are Obscure in the source code; ii) they have a unique monitoring rate and iii) they are forced to have a pre-determined execution order. These characteristics lead to difficulties in maintenance, evolution and often problems related to performance. Design decisions that lead to these difficulties can be characterized as architectural smells. The documentation of smells helps developers identifying refactoring opportunities of a system and also highlights practices that should be analyzed during the design and development of new systems. Therefore, this master thesis proses two architectural smells for adaptive systems: the Obscure Monitor and Oppressed Monitors. The first occurs when the monitors are not evident in the system and the second occurs when the monitors are subject to the same monitoring rate and have a strict execution order. In order to check the influence of the presence of theses smells five maintenance activities were applied in two versions of a system called PhoneAdapter, the original version with the presence of the smells and the refactored one in which the smells were removed. The results indicate that the maintenance and evolution of the refactored system are facilitated in most activities. / Sistemas Adaptativos são capazes de se adaptarem às mudanças de seu ambiente de execução ou das necessidades do usuário. Monitores são essenciais para o desenvolvimento desse tipo de sistema, pois, são responsáveis por coletar e preprocessar dados do contexto. Em um levantamento de sistemas realizado em repositórios e na literatura especializada, notou-se que monitores são por vezes projetados e implementados de uma forma inadequada, exibindo as seguintes características: i) ficam obscuros no código-fonte; ii) possuem uma taxa de monitoramento única e iii) são forçados a ter uma ordem de execução pré-determinada. Isso leva a dificuldades na manutenção, evolução e muitas vezes problemas relacionados a desempenho. Decisões de projetos que levam a essas dificuldades podem ser caracterizadas como smells arquiteturais. A documentação de smells auxilia desenvolvedores a identificar oportunidades de refatorações do sistema, bem como evidenciar práticas que devem ser avaliadas durante o projeto e desenvolvimento de novos sistemas. Portanto, nesta dissertação de mestrado são propostos dois smells arquiteturais: o Obscure Monitor e o Oppressed Monitors. O primeiro ocorre quando os monitores não estão evidentes no sistema e o segundo ocorre quando os monitores estão sujeitos a uma mesma taxa de monitoramento e também possuem uma ordem de execução rígida. Como avaliação preliminar foi realizado um estudo exploratório em um sistema adaptativo chamado PhoneAdapter. Para verificar a influência da presença desses smells foram realizadas cinco atividades de manutenção em duas versões desse sistema, a original com os smells e uma refatorada na qual os smells foram removidos. Os resultados obtidos indicam que a manutenção e evolução de tais sistemas são facilitadas na maioria dessas atividades.

A (self-) adaptive system is a system that can dynamically adapt its behavior or structure during execution to "adapt" to changes to its environment or the system itself. From a security standpoint, there has been some research pertaining to (self-) adaptive systems in general but not enough care has been shown towards the adaptation itself. Security of systems can be reasoned about using threat models to discover security issues in the system. Essentially that entails abstracting away details not relevant to the security of the system in order to focus on the important aspects related to security. Threat models often enable us to reason about the security of a system quantitatively using security metrics. The structural adaptation process of a (self-) adaptive system occurs based on a reconfiguration plan, a set of steps to follow from the initial state (configuration) to the final state. Usually, the reconfiguration plan consists of multiple strategies for the structural adaptation process and each strategy consists of several steps steps with each step representing a specific configuration of the (self-) adaptive system. Different reconfiguration strategies have different security levels as each strategy consists of a different sequence configuration with different security levels. To the best of our knowledge, there exist no approaches which aim to guide the reconfiguration process in order to select the most secure available reconfiguration strategy, and the explicit security of the issues associated with the structural reconfiguration process itself has not been studied. In this work, based on an in-depth literature survey, we aim to propose several metrics to measure the security of configurations, reconfiguration strategies and reconfiguration plans based on graph-based threat models. Additionally, we have implemented a prototype to demonstrate our approach and automate the process. Finally, we have evaluated our approach based on a case study of our making. The preliminary results tend to expose certain security issues during the structural adaptation process and exhibit the effectiveness of our proposed metrics.

Adaptation enables a reaction to a changing environment. For traditional software development, that means changing the design and implementation of the software in a potentially complex and expensive process. If requirements are not known until the runtime of a software system, this system must be able to cope with changes during its runtime. For this, self-adaptive systems (SAS) were created. They have internal knowledge about themselves and their environment to reason about changes and take appropriate actions. Many approaches aiming to build such systems have been published since the start of the research area at the beginning of the 21st century. However, it is difficult to find an appropriate approach, even when all requirements of a scenario the system should be built for are known. If no suitable approach can be found, software developers have to built a new system leading to high development costs and potentially inefficient solutions due to the complexity of the system. This thesis follows two goals: (1) To make approaches building SAS more comparable through a feature model describing features of SAS, and (2) to provide a novel way of specifying SAS concisely using reference attribute grammars (RAGs) providing efficient systems. RAGs originate from the research field of compiler construction and enable the concise description of parts of the internal knowledge mentioned above as well as of the computation of the actions to cope with recognised changes. To make RAGs fully usable, this thesis presents two extensions: Relational RAGs enable the efficient handling of relations required for knowledge graphs, and Connected RAGs let RAG-based system communicate with other external systems to both recognise changes and execute actions. To evaluate the novel approaches, a classification of 30 approaches for the feature model and several case studies in the areas smart home, robotics, and system orchestration were conducted. It can be shown, that significantly less code is required to specify SAS. To specify the computation, 14.5 % to 28.7 % less code was required, whereas in another case study only 6.3 % of the total code was manually written and the rest was generated. The efficiency is similar to the best comparable approaches for graph queries. Furthermore, using additional optimizations (incremental evaluation), the execution time can be shown to be faster by a factor of 167.88 less albeit being sometimes by 50.0 % slower for very small workloads and specific queries. In a more realistic, extrapolated experiment, using incremental evaluation creates speed-up factors between 6.63 and 44.93. With the contributions in this thesis, existing approaches can be selected more precisely, new approaches can classify themselves within the research area, and the development of self-adaptive systems is possible using RAG-based systems.