Um framework orientado a objetos para controladores de trens tolerantes a falhas

Orientador: Cecilia Mary Fischer RubiraDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Este trabalho baseia-se nos conceitos de orientação a objetos, frameworks, estilos de arquitetura, padrões de projeto e metapadrões, para o projeto e implementação de um framework orientado a objetos para controladores de trens tolerantes a falhas e distribuídos. O principal objetivo é a obtenção de reutilização de software em larga escala, com reutilização tanto de código quanto de todo o projeto de software. No desenvolvimento do framework, nós utilizamos estilos de arquitetura para o projeto da sua parte fixa, e padrões de projeto e metapadrões para a documentação da sua parte adaptável. Nosso objetivo é avaliar as vantagens e desvantagens obtidas na aplicação destas técnicas na construção de frameworks. Este trabalho apresenta também propostas de novos padrões de projeto e estilos de arquitetura, que foram utilizados para resolver problemas do domínio do framework. A principal contribuição dos padrões e estilos é a utilização de reflexão computacional na implementação de tolerância a falhas, com o objetivo de obter estruturas de projeto mais flexíveis, o que é uma característica essencial para obtenção de frameworks realmente reutilizáveis.Abstract: This work is based on the concepts of object-orientation, frameworks, architectural styles, design pattems and metapattems to the design and implementation of an object-oriented framework for fault-tolerant train controlers. The main goal is to obtain large-scale reuse, reusing not only the code but also the whole software design. In the framework development, we have applied architectural styles in the design of its fixed parts, and design pattems and metapattems in the design of its adaptable parts. Our goal is to evaluate the advantages and disadvantages of applying these tecniques in the framework construction. This work also presents new design pattems and architectural styles that have been used to solve problems in the framework domain. The main contribution of the pattems and styles is the use of computational reflection in the fault tolerance implementation in order to achieve more adaptable design structure, which is an essential feature of frameworks.MestradoMestre em Ciência da Computaçã

Realising Variability in Dynamic Software Product Line Solutions

Modern systems need to be able to self-adapt to changes in user needs, and changes affecting the system itself or its environment. Dynamic software product line (DSPL) is an engineering approach for developing self-adaptive systems based on commonalities and variabilities for a family of similar systems. Currently, many DSPL approaches fail to meet all adaptability requirements, and in many cases, they are developed in a such unstructured manner that the controller is not explicitly represented, for example. We specify a two-dimension taxonomy to address basic technical issues for realising variability in DSPLs. The self-adaptation dimension classifies the different design choices for the adaptability requirements. The DSPL variability dimension classifies different design choices for implementing variability schemes and for creating different kinds of feature models. Our study was substantiated by surveying several DSPL approaches, and evaluating and comparing their different design strategies. We also summarise practical issues and difficulties, identify major trends in actual DSPL proposals, and suggest directions for future

Representing Variability in Software Architecture: A Systematic Literature Review

Variability in software - intensive systems is the ability of a software artefact (e.g., a system, subsystem, or component) to be extended, customised or configured for deployment in a specific context. Software Architecture is a high - level description of a software - intensive system that abstracts the system implementation details allowing the architect to view the system as a whole. Although variability in software architecture is recognised as a challenge in multiple domains, there has been no formal consensus on how variability should be captured or represented. The objective of this research was to provide a snapshot of the state - of - the - art on representing variability in software architecture while assessing the nature of the different approaches. To achieve this objective, a Systematic Literature Review (SLR) was conducted covering literature produced from January 1991 until June 2016. Then, grounded theory was used to conduct the analysis and draw conclusions from data, mini mising threats to validity. In this paper , we report on the findings from the study

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Risk-Based Decision Support Framework for Managing Excessive Geometric Variability Issues in Modular Construction

Managing and controlling excessive dimensional and geometrical variability (i.e., tolerances) of modular components and assemblies during the fabrication, transportation, and erection phases, represents a major issue in modular construction (MC) projects. The current industry practices manage tolerance-related risks either reactively (e.g., onsite adjustment by applying forces, shimming, and replacing defected components), or proactively (e.g., 2D & 3D jigs, prototyping (mock-ups), and 3D laser scanning technology, and tolerance theory). The reactive approaches include expensive and time-consuming field rework, schedule delays, and serviceability or functional failures. On the other hand, the proactive approaches require a significant amount of investment (resources) during early project phases (design and fabrication) to produce modular systems that are compliant with design specifications. Thus, improper assessment and reactive management of excessive geometric variabilities due to out-of-tolerances can result in extensive site-fit rework, cost overruns, schedule delays, quality issues, and owner dissatisfaction. The perceived risks and challenges will continue to fuel the reluctance of industry practitioners to apply modularization in future construction projects. Therefore, different decision support systems (DSSs), frameworks, decision matrices, models, and toolkits have been developed to evaluate modularization feasibility (benefits and challenges) for construction projects during early project phases. However, these DSSs, frameworks, and toolkits are not without their limitations. Most previously developed DSSs and toolkits focus on: 1) strategic and high-level decisions; 2) general modularization risks ; and 3) reactive solutions. Also, these DSSs and toolkits lack: 1) quantitative and probabilistic risk assessment techniques to evaluate the modularization risk impact on the overall project performance (cost, schedule, quality, etc.); 2) consideration of the impact of the unique relationships (propagation behaviour and cause-effect relationship) among risks in decision making process; and 3) integration of dynamic risk assessment and management techniques to revise the risk management plans as more accurate modularization process capability information becomes available. With this in mind, further efforts are needed to systematically evaluate tolerance-related risks and excessive geometric variability issues, and proactively manage their impact, both of which are expected to improve modularization performance and maximize its benefits in construction projects. The goals of the research presented in this research are to develop: 1) a systematic process to identify, quantitatively evaluate, and proactively manage tolerance-related risks by identifying optimum geometric variability (using a strict or relaxed tolerance approach) that will achieve cost efficiency requirements; 2) an efficient approach to thoroughly evaluate and manage tolerance-related risks at local and global levels by incorporating the propagation behaviour and cause-effect relationships among risks in the decision making process; and 3) a dynamic methodology to continually evaluate tolerance-based risk management plans and revise risk response decisions as new information becomes available. The results of the work conducted for this research study contribute to both knowledge and practice. On the knowledge side, the main contribution is the introduction of an efficient risk management methodology, which will support modularization decision-making process with respect to the selection of optimum approaches to proactively manage tolerance-related risks and excessive geometric variability issues in construction projects. On the practice side, this research will enhance in a quantitative and proactive manner our understanding of the unique risks and challenges associated with MC, which will help the stakeholders, including project risk managers, decision makers, and construction managers, to improve modularization performance and maximize its benefits

An orthogonal framework for fault tolerance composition in software systems

Building reliable systems is one of the major challenges faced by software developers as society is becoming more dependent on software systems. The failure of any system can lead to a serious loss, for example serious injury or death in case of safety critical systems and significant financial loss in the case of business-critical systems. As a consequence, fault tolerance is considered as a solution to provide reliability, but the fault tolerance capability is associated with many challenges, such as the right development phase where it needs to be introduced, how it can be composed with the software, and the issues that arise from this composition such as complexity and potential undesirable feature interactions. This thesis presents an orthogonal fault tolerance framework for the composition of design diversity fault tolerance mechanism with the base system. It further ensures the separation of concerns between the ‘base’ system and the fault tolerance mechanisms that are composed with the base system. The composition in this framework is based on operational semantics that describe the behaviour of the underlying components when composed with the fault tolerance mechanisms. A custom-built pre-processor is based on these composition rules, and is used to automatically compose the system component and the fault tolerance mechanisms. The very introduction of different fault tolerance mechanisms to the system may cause interactions with other fault tolerance features or with system components. Logic properties written in CTL and LTL are used in NuSMV to analyse undesirable interactions. To illustrate its applicability, the framework has been applied to the Home Automation and Therac-25 software