Ever fiercer competition has forced enterprises not only to optimize their own operations but also to cooperate with their suppliers and customers along their supply chains. Thus, competition today usually takes place between supply chains and not between individual enterprises. Business-To-Business integration (B2Bi) is a major task of supply chain management (SCM), and although it already has been researched for years, B2Bi is still an area of active research with a plethora of research questions and according approaches. Hence, management of B2Bi projects necessitates the identification of relevant requirements which is a far from trivial task. This paper identifies a core set of B2Bi challenges and deduces a comprehensive set of B2Bi requirements that are particularly useful for tackling the challenges identified. The derivation of B2Bi requirements follows an inductive approach that is based on the analysis of integration standards, reference architectures and related literature. In order to operationalize the B2Bi requirements for further analysis and concrete B2Bi projects, the requirements are classified according to the abstraction layers of a B2Bi schema. Thus, this report not only offers a requirements check list for B2Bi projects but also helps in deciding when to address which requirements during the course of a B2Bi project.
Die Geschäftsprozessmodellierung hat sich in der Praxis als Grundlage für die Ableitung fachlicher Anforderungen an betriebliche Anwendungssysteme weitgehend etabliert. Die anschließende Übertragung der fachlichen Modelle auf eine software-technische Implementierungsplattform bedeutet hingegen häufig einen methodischen Bruch und ist daher sehr aufwändig sowie komplex. Eine software-technische Implementierungsplattform, deren Konzepte sich an den Fachkonzepten der Geschäftsprozessmodellierung orientieren, kann diesen Übergang vereinfachen und die Systementwicklungsaufgabe hinsichtlich Aufwand und Komplexität deutlich verringern. Die vorliegende Arbeit beschreibt die Konzeption und Realisierung eines Software-Frameworks als flexible Basismaschine für die Entwicklung betrieblicher Anwendungssysteme auf Basis der SOM-Methodik. Das Framework bietet ausgehend von den fachlichen Modellen des Anwendungssystems anwendungsneutrale Software-Komponenten zu dessen vollständiger software-technischer Abbildung.
During the last decades, information technology has been characterized by constantly increasing performance of available hardware resources. This development allows the assignment of more and more complex tasks to software systems while at the same time leading to a massive increase of inherent complexity of applied systems. The expected further increase of complexity in the future demands for an explicit addressing of complexity. The concept of Component Orientation represents an approach for complexity reduction during the development and configuration of software through functional decomposition. With the vision of Autonomic Computing there does exist an approach for addressing complexity during the operation and maintenance of software systems. In this context, the approach is based on the idea of assigning low level-management tasks to the managed system itself. The concept of Component Orientation leads to the establishment of system architectures out of clearly distinguishable building blocks. Therefore, Component Orientation seems to provide a promising foundation for realizing the vision of Autonomic Computing. This thesis presents a realistic infrastructure for the autonomic management of component-based enterprise systems. The application area of such systems leads to special requirements for managed systems and is highly affected by the complexity problem. As a foundation for the proposed approach, a well established component standard was chosen to guarantee the practical relevance of applied concepts and techniques. The applied standard is Enterprise JavaBeans, version 3.0. The proposed infrastructure is designed and realized in a generic fashion. It provides a platform upon which solutions for different application areas of Autonomic Computing can be realized. Autonomic entities are supported through a programming interface which represents a system on three interrelated levels and allows its management: On the top-level, the underlying software of a managed system is considered. The middle layer addresses the system architecture. Runtime interactions within the system are represented on the lowest layer. On this foundation, a system can be managed in a holistic, model-based way. The runtime management of a system is enabled through a specially developed component which must be integrated into the affected environment. This component is compliant with the applied component standard and does not require any adjustment of the underlying component platform. Finally, a tool is provided which supports the establishment of manageability through the automated execution of required adjustments of components. The management of a system is realized transparently for its constituent elements during runtime. On the whole, the development of enterprise software is not affected by a potential application of the presented infrastructure.
Inductive programming is concerned with the automated construction of declarative, often functional, recursive programs from incomplete specifications such as input/output examples. The inferred program must be correct with respect to the provided examples in a generalising sense: it should be neither equivalent to them, nor inconsistent. Inductive programming algorithms are guided explicitly or implicitly by a language bias (the class of programs that can be induced) and a search bias (determining which generalised program is constructed first). Induction strategies are either generate-and-test or example-driven. In generate-and-test approaches, hypotheses about candidate programs are generated independently from the given specifications. Program candidates are tested against the given specification and one or more of the best evaluated candidates are developed further. In analytical approaches, candidate programs are constructed in an example-driven way. While generate-and-test approaches can -- in principle -- construct any kind of program, analytical approaches have a more limited scope. On the other hand, efficiency of induction is much higher in analytical approaches. Inductive programming is still mainly a topic of basic research, exploring how the intellectual ability of humans to infer generalised recursive procedures from incomplete evidence can be captured in the form of synthesis methods. Intended applications are mainly in the domain of programming assistance -- either to relieve professional programmers from routine tasks or to enable non-programmers to some limited form of end-user programming. Furthermore, in the future, inductive programming techniques might be applied to further areas such as supporting the inference of lemmata in theorem proving or learning grammar rules. Inductive automated program construction has been originally addressed by researchers in artificial intelligence and machine learning. During the last years, some work on exploiting induction techniques has been started also in the functional programming community. Therefore, the third workshop on |Approaches and Applications of Inductive Programming| took place for the first time in conjunction with the ACM SIGPLAN International Conference on Functional Programming (ICFP 2009). The first and second workshop were associated with the International Conference on Machine Learning (ICML 2005) and the European Conference on Machine Learning (ECML 2007). AAIP´09 aimed to bring together researchers from the functional programming and the artificial intelligence communities, working in the field of inductive functional programming, and advance fruitful interactions between these communities with respect to programming techniques for inductive programming algorithms, the identification of challenge problems and potential applications. For everybody interested in inductive programming we recommend to visit the website: www.inductive-programming.org.
The so-called 'healthy immigrant effect' (HIE) is one of the most striking findings concerning immigrants and their health status. It is usually said to consist of two parts: According to the first part, immigrants upon arrival are on average healthier than their native peers. This finding is mostly explained by self-selection among their origin population. The idea is that healthier individuals are more likely to migrate as they are more able to reap the reward of the investment ‘migration’ than less healthy individuals. However, according to the second part, this health gap between immigrants and natives closes after a relatively short period of time, and the health of immigrants is converging to that of the natives or is getting even worse. This gradient of immigrants’ health has been found in many countries (e.g., Australia, Canada, and the United States) and for many different measures of health (e.g., self-rated health, chronic diseases). The causes for this decline in immigrants’ health are subject to ongoing research, but the underlying processes are not yet fully understood. In literature, several different explanations are discussed: The adoption of destination-country habits and lifestyles, the structural and material relationship between a low socio-economic status and poor health, additional stress due to the migration process, persistent barriers to access to health care due to cultural or language factors, as well as a kind of 'statistical artefact' due to selection effects caused by return migration. As health is a rather complex concept, one can assume that none of the proposed explanations can solely explain the decline in immigrants’ health, but rather that the health deterioration is a result of different interacting causes. This thesis investigates three of the proposed possible explanations for a decline in immigrants’ health, namely return migration, the adoption of destination-country habits and lifestyles, and immigrants’ access to health care and utilisation of health care services.