Dependability verification for contextual/runtime goal modelling

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2015.Um contexto de operação estático não é a realidade para muitos sistemas de software atualmente. Variações de contextos impõe novos desafios ao desenvolvimento de sistemas seguros, o que inclui a ativação de falhas apenas em contextos específicos de operação. A engenharia de requisitos orientada a objetivos (GORE) explicita o ‘por quê’ dos requisitos de um sistema, isto é, a intencionalidade por trás de objetivos do sistema e os meios de se atingi-los. Um Runtime goal model (RGM) adiciona especificação de comportamento ao modelo de objetivos convencional, enquanto um Contextual goal model (CGM) especifica efeitos de contextos sobre objetivos, meios e métricas de qualidade. Visando uma verificação formal da dependabilidade de um Contextual-Runtime goal model (CRGM), nesse trabalho é proposta uma nova abordagem para a análise de dependabilidade orientada a objetivos baseada na técnica de verificação probabilística de modelos. Em particular, são definidas regras para a transformação de um CRGM para um modelo cadeia de Makov de tempo discreto (DTMC) com o qual se possa verificar a confiabilidade de se satisfazer um ou mais objetivos do sistema. Adicionalmente, para diminuir o esforço de análise e aumentar a usabilidade de nossa proposta, um gerador automatizado de código CRGM para DTMC foi implementado e integrado com sucesso à ferramenta gráfica que dá suporte às fases de modelagem e análise de objetivos da metodologia TROPOS. A verificação contextual de dependabilidade resultante reflete os requisitos no CRGM, que podem representar: o projeto de um sistema, cuja verificação ocorreria em fase de projetos; ou um sistema em execução, cujo comportamento pode ser verificado em tempo de execução como parte de uma análise de auto-adaptação com foco em dependabilidade.A static and stable operation environment is not a reality for many systems nowadays. Context variations impose many threats to systems safety, including the activation of context specific failures. Goal-oriented requirements engineering (GORE) brings forward the ‘why’ of system requirements, i.e., the intentionality behind system goals and the means to meet then. A runtime goal model adds a behaviour specification layer to a conventional design goal model, and a contextual goal model specifies the context effects over system goals, means and qualitative metrics. In order to formally verify the dependability of a CRGM, we propose a new goal-oriented dependability analysis based on the probabilistic model checking technique. In particular, we define rules for the transformation of a CRGM into a DTMC model that can be verified for the reliability of the fulfilment of one or more system goals. Also, to mitigate the analysis overhead and increase the usability of our proposal, we have successfully implemented and integrated a CRGM to DTMC code generator to the graphical tool that supports the goal modelling and analysis phases of the TROPOS development methodology. The resulting contextual dependability verification reflects the system requirements in a CRGM, which may represent: a system-to-be, whose verification would take place at design-time; or a running system, whose behaviour can be verified at runtime as part of a self-adaptation analysis targeting dependability

GODA: A goal-oriented requirements engineering framework for runtime dependability analysis

Many modern software systems must deal with changes and uncertainty. Traditional dependability requirements engineering is not equipped for this since it assumes that the context in which a system operates be stable and deterministic, which often leads to failures and recurrent corrective maintenance. The Contextual Goal Model (CGM), a requirements model that proposes the idea of context-dependent goal fulfillment, mitigates the problem by relating alternative strategies for achieving goals to the space of context changes. Additionally, the Runtime Goal Model (RGM) adds behavioral constraints to the fulfillment of goals that may be checked against system execution traces. Objective: This paper proposes GODA (Goal-Oriented Dependability Analysis) and its supporting framework as concrete means for reasoning about the dependability requirements of systems that operate in dynamic contexts. Method: GODA blends the power of CGM, RGM and probabilistic model checking to provide a formal requirements specification and verification solution. At design time, it can help with design and implementation decisions; at runtime it helps the system self-adapt by analyzing the different alternatives and selecting the one with the highest probability for the system to be dependable. GODA is integrated into TAO4ME, a state-of-the-art tool for goal modeling and analysis. Results: GODA has been evaluated against feasibility and scalability on Mobee: a real-life software system that allows people to share live and updated information about public transportation via mobile devices, and on larger goal models. GODA can verify, at runtime, up to two thousand leaf-tasks in less than 35ms, and requires less than 240 KB of memory. Conclusion: Presented results show GODA's design-time and runtime verification capabilities, even under limited computational resources, and the scalability of the proposed solution

A3Droid: A framework for developing distributed crowdsensing

The amount and diversity of sensors on modern mobile devices, together with the computing performance that these devices can guarantee, make crowdsensing an important alternative to traditional sensor networks. Crowdsensing applications often exploit server-side components to aggregate, correlate, and manipulate the data collected my the mobile devices in the field. We advocate that this architecture limits the scenarios in which crowdsensing can be applied. Instead, we believe that crowdsensing should transition to a distributed foglike architecture, in which edge devices can be made responsible for most of the computation that needs to be achieved. In this paper we present A3Droid, a framework for developing crowdsensing applications for the Android platform. It supports a fog-like architecture, and helps the developer create robust and scalable applications that can collect and use high-quality data from the field. A3Droid was evaluated in a lab experiment that mimics a scenario in which geo-located data are collected from moving buses to gather up-to-date information about a city's traffic

A unified model for the mobile-edge-cloud continuum

Technologies such as mobile, edge, and cloud computing have the potential to form a computing continuum for new, disruptive applications. At runtime, applications can choose to execute parts of their logic on different infrastructures that constitute the continuum, with the goal of minimizing latency and battery consumption and maximizing availability. In this article, we propose A3-E, a unified model for managing the life cycle of continuum applications. In particular, A3-E exploits the Functions-as-a-Service model to bring computation to the continuum in the form of microservices. Furthermore, A3-E selects where to execute a certain function based on the specific context and user requirements. The article also presents a prototype framework that implements the concepts behind A3-E. Results show that A3-E is capable of dynamically deploying microservices and routing the application’s requests, reducing latency by up to 90% when using edge instead of cloud resources, and battery consumption by 74% when computation has been offloaded.Fil: Baresi, Luciano. Politecnico di Milano; ItaliaFil: Mendonça, Danilo Filgueira. Politecnico di Milano; ItaliaFil: Garriga, Martín. Politecnico di Milano; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Guinea, Sam. Politecnico di Milano; ItaliaFil: Quattrocchi, Giovanni. Politecnico di Milano; Itali