Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

Visualization of Business Process Modeling Anti Patterns

Patterns are used to capture and document frequent design activities. Patterns are means to compare the expressiveness of different modeling languages. On the other hand, the term $anti-pattern$ points to undesirable design activities. In the field of business process modeling, useful patterns were collected to help evaluate models and tools. Nevertheless, there was almost no work to capture the unwanted design patterns. The most common way to model business processes is to use a graphical modeling language. The most widespread notation are business process diagrams modeled in the language BPMN. In this paper, we formalize structural patterns that can lead to control flow errors in such graphical models. For expressing such error patterns, we use the visual query language BPMN-Q . By using a query processor, a business process modeler is able to identify possible errors in business process diagrams. Moreover, the erroneous parts of the business process diagram can be highlighted when an instance of an error pattern is found. This way, the modeler gets an easy-to-understand feedback in the visual modeling language he or she is familiar with

Improving the Usability of OCL as an Ad-hoc Model Querying Language

Abstract. The OCL is often perceived as difficult to learn and use. In previous research, we have defined experimental query languages exhibiting higher levels of usability than OCL. However, none of these alternatives can rival OCL in terms of adoption and support. In an attempt to leverage the lessons learned from our research and make it accessible to the OCL community, we propose the OCL Query API (OQAPI), a library of query-predicates to improve the user-friendliness of OCL for ad-hoc querying. The usability of OQAPI is studied using controlled experiments. We find considerable evidence to support our claim that OQAPI facilitates user querying using OCL.

Database Localization in a Test Environment

One of the most significant challenges facing database software publishers is globalizing their products to tap into potentially profitable overseas business opportunities. The challenges of making products work overseas are many, ranging from budgeting for globalization projects to requiring developers to be skilled in localization. Over the years, software publishers have developed and implemented various tools and processes for globalization and localization. While there is considerable literature available on software development lifecycles and case studies, few studies have focused on globalization of database software. This thesis will examine the extent to which database publishers are using internationalization tools and processes to help them solve globalization challenges. Thesis deliverables will be specified tool evaluations and workarounds for database localization

A contribution for data processing and interoperability in Industry 4.0

Dissertação de mestrado em Engenharia de SistemasIndustry 4.0 is expected to drive a significant change in companies’ growth. The idea is to cluster important information from all the company’s supply chain, enabling valuable decision-making while permitting interactions between machines and humans in real time. Autonomous systems powered with Information Technologies are enablers of Industry 4.0 – like Internet of Things (IoT), Cyber Physical-Systems (CPS) and Big Data and analytics. IoT gather information from every piece of the big puzzle which is the manufacturing process. Cloud Computing store all that information in one place. People share information across the company, between its supply chain and hierarchical levels through integration of systems. Finally, Big Data and analytics are of intelligence that will improve Industry 4.0. Methods and tools in Industry 4.0 are designed to increase interoperability across industrial stakeholders. In order to make the complete process possible, standardisation must be implemented across the company. Two reference models for Industry 4.0 were studied - RAMI 4.0 and IIRA. RAMI 4.0, a German initiative, focuses on industrial digitalization while IIRA, an American initiative, focuses on “Internet of Things” world, i.e. energy, healthcare and transportation. The two initiatives aim to obtain intelligence data from processes while enabling interoperability among systems. Representatives from the two reference models are working together on the technological interface standards that could be used by companies joining this new era. This study aims at the interoperability between systems. Even though there must be a model to guide the company into Industry 4.0, this model ought to be mutable and flexible enough to handle differences in manufacturing process, as an example automotive industry 4.0 will not have the same approach as aviation Industry 4.0.Espera-se que a Indústria 4.0 seja uma mudança significativa no crescimento das empresas. O objetivo é agrupar informações importantes de toda a cadeia de suprimentos da empresa, proporcionando uma tomada de decisão mais acertada, ao mesmo tempo que permite interações entre seres humanos e máquinas em tempo real. Sistemas autônomos equipados com Tecnologias da Informação possibilitam a Indústria 4.0 como a Internet das Coisas (IoT), sistemas ciber-físicos (CPS) e Big Data e analytics. A IoT coleta informações de cada peça do grande quebra-cabeça que é o processo de fabricação. Cloud Computing lida com armazenamento de toda essa informação em um só lugar. As pessoas compartilham informações em toda a empresa, na cadeia de abastecimento e níveis hierárquicos por meio da integração de sistemas. Por fim, Big Data e analytics são de inteligência que melhorarão a Indústria 4.0. Os métodos e ferramentas da Indústria 4.0 são projetadas para aumentar a interoperabilidade entre os stakeholders. Para tornar possível essa interoperabilidade, um padrão em toda a empresa deve ser implementado. Dois modelos de referência para a Indústria 4.0 foram estudados - RAMI 4.0 e IIRA. RAMI 4.0, a iniciativa alemã, concentra-se na digitalização industrial, enquanto IIRA, a iniciativa americana, foca no mundo da Internet das Coisas, como energia, saúde e transporte. As duas iniciativas visam obter dados inteligentes dos processos e, ao mesmo tempo, permitir a interoperabilidade entre os sistemas. Representantes dos dois modelos de referência estão a trabalhar juntos para discutir os padrões de interface tecnológica que podem ser usados pelas empresas que entram nessa nova era. Este estudo visa a interoperabilidade entre sistemas. Embora deva haver um modelo para orientar a empresa na Indústria 4.0, esse modelo deve ser mutável e flexível o suficiente para lidar com diferenças no processo de fabricação, como exemplo a indústria 4.0 automotiva não terá a mesma abordagem que a Indústria 4.0 de aviação