17 research outputs found

    Impact-Analyse fĂĽr AspectJ - Eine kritische Analyse mit werkzeuggestĂĽtztem Ansatz

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    Aspect-Oriented Programming (AOP) has been promoted as a solution for modularization problems known as the tyranny of the dominant decomposition in literature. However, when analyzing AOP languages it can be doubted that uncontrolled AOP is indeed a silver bullet. The contributions of the work presented in this thesis are twofold. First, we critically analyze AOP language constructs and their effects on program semantics to sensitize programmers and researchers to resulting problems. We further demonstrate that AOP—as available in AspectJ and similar languages—can easily result in less understandable, less evolvable, and thus error prone code—quite opposite to its claims. Second, we examine how tools relying on both static and dynamic program analysis can help to detect problematical usage of aspect-oriented constructs. We propose to use change impact analysis techniques to both automatically determine the impact of aspects and to deal with AOP system evolution. We further introduce an analysis technique to detect potential semantical issues related to undefined advice precedence. The thesis concludes with an overview of available open source AspectJ systems and an assessment of aspect-oriented programming considering both fundamentals of software engineering and the contents of this thesis

    Disciplined Reuse of Aspects (State of the Art & Work Plan)

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    This document describes the work plan and state of the art for the PhD work of André Restivo started in 2006. Acceptance of this document by a steering committee is mandatory for the final registration in the Doctoral Programme in Informatics Engineering (ProDEI) at the Engineering Faculty of University of Porto

    Mining a Small Medical Data Set by Integrating the Decision Tree and t-test

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    [[abstract]]Although several researchers have used statistical methods to prove that aspiration followed by the injection of 95% ethanol left in situ (retention) is an effective treatment for ovarian endometriomas, very few discuss the different conditions that could generate different recovery rates for the patients. Therefore, this study adopts the statistical method and decision tree techniques together to analyze the postoperative status of ovarian endometriosis patients under different conditions. Since our collected data set is small, containing only 212 records, we use all of these data as the training data. Therefore, instead of using a resultant tree to generate rules directly, we use the value of each node as a cut point to generate all possible rules from the tree first. Then, using t-test, we verify the rules to discover some useful description rules after all possible rules from the tree have been generated. Experimental results show that our approach can find some new interesting knowledge about recurrent ovarian endometriomas under different conditions.[[journaltype]]國外[[incitationindex]]EI[[booktype]]紙本[[countrycodes]]FI

    Engineering holistic fault tolerance

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    PhD ThesisFault-tolerant software should be engineered to be maintainable as well as efficient with regards to performance and resources. These characteristics should be evaluated before deployment of the software. However, the main focus is very often made on the functional features of the application, whereas fault tolerance mechanisms are neglected. As a result, they are often neither maintainable nor efficient. The concept of Holistic Fault Tolerance was introduced to deal with these issues. It is a novel crosscutting approach to the design and implementation of fault tolerance mechanisms for developing reliable software applications that meet non-functional requirements, such as performance and resource utilisation. The thesis starts with the description of problems that were motivating for the idea of Holistic Fault Tolerance. These problems are related to resource utilisation requirements of modern computer-based systems, since more resources like hardware components and energy are required to process modern computational tasks and ensure performance and reliability of the computation. Moreover, the complexity of these systems grows, leading to maintainability deterioration, especially of those system parts, which are responsible for satisfying non-functional requirements, such as reliability, performance and resource usage. After analysis of the problems and motivations, the engineering approach to Holistic Fault Tolerance is introduced and main engineering steps are defined. Next, an architectural pattern for Holistic Fault Tolerance is presented. The method to refine the proposed architecture and ensure efficiency of a particular system under development is demonstrated during the modelling step. Then the implementation of Holistic Fault Tolerance based on the proposed architecture and modelling is described in detail. Finally, the Holistic Fault Tolerance architecture is evaluated with regards to efficiency and maintainability. The evaluation demonstrates that Holistic Fault Tolerance assists in meeting the non-functional requirements, makes fault tolerance mechanisms easier to maintain and ensures higher modularity of the source cod

    Mutation Testing Advances: An Analysis and Survey

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    Achieving Autonomic Web Service Compositions with Models at Runtime

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    Over the last years, Web services have become increasingly popular. It is because they allow businesses to share data and business process (BP) logic through a programmatic interface across networks. In order to reach the full potential of Web services, they can be combined to achieve specifi c functionalities. Web services run in complex contexts where arising events may compromise the quality of the system (e.g. a sudden security attack). As a result, it is desirable to count on mechanisms to adapt Web service compositions (or simply called service compositions) according to problematic events in the context. Since critical systems may require prompt responses, manual adaptations are unfeasible in large and intricate service compositions. Thus, it is suitable to have autonomic mechanisms to guide their self-adaptation. One way to achieve this is by implementing variability constructs at the language level. However, this approach may become tedious, difficult to manage, and error-prone as the number of con figurations for the service composition grows. The goal of this thesis is to provide a model-driven framework to guide autonomic adjustments of context-aware service compositions. This framework spans over design time and runtime to face arising known and unknown context events (i.e., foreseen and unforeseen at design time) in the close and open worlds respectively. At design time, we propose a methodology for creating the models that guide autonomic changes. Since Service-Oriented Architecture (SOA) lacks support for systematic reuse of service operations, we represent service operations as Software Product Line (SPL) features in a variability model. As a result, our approach can support the construction of service composition families in mass production-environments. In order to reach optimum adaptations, the variability model and its possible con figurations are verifi ed at design time using Constraint Programming (CP). At runtime, when problematic events arise in the context, the variability model is leveraged for guiding autonomic changes of the service composition. The activation and deactivation of features in the variability model result in changes in a composition model that abstracts the underlying service composition. Changes in the variability model are refl ected into the service composition by adding or removing fragments of Business Process Execution Language (WS-BPEL) code, which are deployed at runtime. Model-driven strategies guide the safe migration of running service composition instances. Under the closed-world assumption, the possible context events are fully known at design time. These events will eventually trigger the dynamic adaptation of the service composition. Nevertheless, it is diffi cult to foresee all the possible situations arising in uncertain contexts where service compositions run. Therefore, we extend our framework to cover the dynamic evolution of service compositions to deal with unexpected events in the open world. If model adaptations cannot solve uncertainty, the supporting models self-evolve according to abstract tactics that preserve expected requirements.Alférez Salinas, GH. (2013). Achieving Autonomic Web Service Compositions with Models at Runtime [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34672TESI

    Combining SOA and BPM Technologies for Cross-System Process Automation

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    This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation
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