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Generative aspect-oriented component adaptation.

Feng, Yankui (2008) Generative aspect-oriented component adaptation. PhD thesis, Napier University.

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    Abstract/Description

    Due to the availability of components and the diversity of target applications, mismatches between pre-qualified existing components and the particular reuse context in applications are often inevitable and have been a major
    hurdle of component reusability and successful composition. Although component adaptation has acted as a key solution for eliminating these mismatches, existing practices are either only capable for adaptation at the
    interface level, or require too much intervention from software engineers. Another weakness of existing approaches is the lack of reuse of component
    adaptation knowledge.

    Aspect Oriented Programming (AOP) is a new methodology that provides separation of crosscutting concerns by introducing a new unit of modularization - an Aspect that crosscuts other modules. In this way, all the associated complexity of the crosscutting concerns is isolated into the Aspects, hence the final system becomes easier to design, implement and maintain. The nature of AOP makes it particularly suitable for addressing non-functional mismatches with component-based systems. However,
    current AOP techniques are not powerful enough for efficient component adaptation due to the weaknesses they have, including the limited reusability of Aspects, platform specific Aspects, and naive weaving processes.
    Therefore, existing AOP technology needs to be expanded before it can be used for efficient component adaptation.

    This thesis presents a highly automated approach to component adaptation through product line based Generative Aspect Oriented Component adaptation. In the approach, the adaptation knowledge is captured in Aspects and aims to be reusable in various adaptation circumstances.

    Automatic generation of adaptation Aspects is developed as a key technology to improve the level of automation of the approach and the reusability of adaptation knowledge. This generation is realised by developing a two dimensional Aspect model, which incorporates the technologies of software product line and generative programming. The
    adaptability and automation of the approach is achieved in an Aspect oriented component adaptation framework by generating and then applying the adaptation Aspects under a designed weaving process according to specific adaptation requirements. To expand the adaptation power of AOP, advanced Aspect weaving processes have been developed with the support of an enhanced aspect weaver. To promote the reusability of adaptation Aspects, an expandable repository of reusable adaptation Aspects has been
    developed based on the proposed two-dimensional Aspect model.

    A prototype tool is built as a leverage of the approach and automates the adaptation process. Case studies have been done to illustrate and evaluate the approach, in terms of its capability of building highly reusable Aspects
    across various AOP platforms and providing advanced weaving process.

    In summary, the proposed approach applies Generative Aspect Oriented Adaptation to targeted components to correct the mismatch problem so that the components can be integrated into a target application easily. The
    automation of the adaptation process, the deep level of the adaptation, and the reusability of adaptation knowledge are the advantages of the approach.

    Item Type: Thesis (PhD)
    Uncontrolled Keywords: Computing; Software; Component adaptation; Aspect-oriented programming; Line-based generative aspect oriented adaptation; Deep adaptation; Enhanced aspect weaver; Reusable adaptation aspects; Reusability of adaptation knowledge;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment
    Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 005 Computer programming, programs & data
    Library of Congress Subjects: Q Science > QA Mathematics > QA76 Computer software
    Item ID: 2431
    Depositing User: Dr. David A. Cumming
    Date Deposited: 09 Oct 2008 09:50
    Last Modified: 27 Sep 2011 11:06
    URI: http://researchrepository.napier.ac.uk/id/eprint/2431

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