Browsing by Subject "Computer software maintenance"

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    Flora: a framework for decomposing software architecture to introduce local recovery
    (John Wiley & Sons Ltd., 2009-07) Sözer, H.; Tekinerdoǧan, B.; Akşit, M.
    The decomposition of software architecture into modular units is usually driven by the required quality concerns. In this paper we focus on the impact of local recovery concern on the decomposition of the software system. For achieving local recovery, the system needs to be decomposed into separate units that can be recovered in isolation. However, it appears that this required decomposition for recovery is usually not aligned with the decomposition based on functional concerns. Moreover, introducing local recovery to a software system, while preserving the existing decomposition, is not trivial and requires substantial development and maintenance effort. To reduce this effort we propose a framework that supports the decomposition and implementation of software architecture for local recovery. The framework provides reusable abstractions for defining recoverable units and the necessary coordination and communication protocols for recovery. We discuss our experiences in the application and evaluation of the framework for introducing local recovery to the open-source media player called MPlayer. Copyright 2009 John Wiley & Sons, Ltd.
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    Market-driven approach based on Markov decision theory for optimal use of resources in software development
    (Institution of Engineering and Technology, 2004) Noppen, J.; Aksit, M.; Nicola, V.; Tekinerdogan, B.
    Changes in requirements may have a severe impact on development processes. For example, if requirements change during the course of a software development activity, it may be necessary to reschedule development activities so that the new requirements can be addressed in a timely manner. Unfortunately, current software development methods do not provide explicit means to adapt development processes with respect to changes in requirements. The paper proposes a method based on Markov decision theory, which determines the estimated optimal development schedule with respect to probabilistic product demands and resource constraints. This method is supported by a tool and applied to an industrial case.