Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach

Goals are first-class entities in a self-adaptive system (SAS) as they guide the self-adaptation. A SAS often operates in dynamic and partially unknown environments, which cause uncertainty that the SAS has to address to achieve its goals. Moreover, besides the environment, other classes of uncertainty have been identified. However, these various classes and their sources are not systematically addressed by current approaches throughout the life cycle of the SAS. In general, uncertainty typically makes the assurance provision of SAS goals exclusively at design time not viable. This calls for an assurance process that spans the whole life cycle of the SAS. In this work, we propose a goal-oriented assurance process that supports taming different sources (within different classes) of uncertainty from defining the goals at design time to performing self-adaptation at runtime. Based on a goal model augmented with uncertainty annotations, we automatically generate parametric symbolic formulae with parameterized uncertainties at design time using symbolic model checking. These formulae and the goal model guide the synthesis of adaptation policies by engineers. At runtime, the generated formulae are evaluated to resolve the uncertainty and to steer the self-adaptation using the policies. In this paper, we focus on reliability and cost properties, for which we evaluate our approach on the Body Sensor Network (BSN) implemented in OpenDaVINCI. The results of the validation are promising and show that our approach is able to systematically tame multiple classes of uncertainty, and that it is effective and efficient in providing assurances for the goals of self-adaptive systems

Methods of Technical Prognostics Applicable to Embedded Systems

Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy. Dizertační práce přináší přehled základních metod použitelných pro účely predikce zbývající užitné životnosti, jsou zde popsány metriky pomocí, kterých je možné jednotlivé přístupy porovnávat ať už z pohledu přesnosti, ale také i z pohledu výpočetní náročnosti. Jedno z dizertačních jader tvoří doporučení a postup pro výběr vhodné prognostické metody s ohledem na prognostická kritéria. Dalším dizertačním jádrem je představení tzv. částicového filtrovaní (particle filtering) vhodné pro model-based prognostiku s ověřením jejich implementace a porovnáním. Hlavní dizertační jádro reprezentuje případovou studii pro velmi aktuální téma prognostiky Li-Ion baterii s ohledem na trvalé monitorování. Případová studie demonstruje proces prognostiky založené na modelu a srovnává možné přístupy jednak pro odhad doby před vybitím baterie, ale také sleduje možné vlivy na degradaci baterie. Součástí práce je základní ověření modelu Li-Ion baterie a návrh prognostického procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

A Quality Model for Actionable Analytics in Rapid Software Development

Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by IEEE in the 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018. The final authenticated version will be available onlin

Pattern-driven security, privacy, dependability and interoperability management of iot environments

Achieving Security, Privacy, Dependability and Interoperability (SPDI) is of paramount importance for the ubiquitous deployment and impact maximization of Internet of Things (IoT) applications. Nevertheless, said requirements are not only difficult to achieve at system initialization, but also hard to prove and maintain at run-time. This paper highlights an approach to tackling the above challenges, through the definition of pattern language and a framework that can guarantee SPDI in IoT orchestrations. By integrating pattern reasoning engines at the various layers of the IoT infrastructure, and a machine-processable representation of said pattern through Drools rules, the proposed framework can provide ways to fulfill SPDI requirements at design time, and also provide the means to guarantee those SPDI properties and manage the orchestrations accordingly. Moreover, an application example of the framework is presented in an Industrial IoT monitoring environment