34,623 research outputs found
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Run-time Support to Manage Architectural Variability Speci ed with CVL
The execution context in which pervasive systems or mobile
computing run changes continuously. Hence, applications for these systems
should be adapted at run-time according to the current context.
In order to implement a context-aware dynamic reconfiguration service,
most approaches usually require to model at design-time both the list of
all possible configurations and the plans to switch among them. In this
paper we present an alternative approach for the automatic run-time generation
of application configurations and the reconfiguration plans. The
generated configurations are optimal regarding di erent criteria, such as
functionality or resource consumption (e.g. battery or memory). This is
achieved by: (1) modelling architectural variability at design-time using
Common Variability Language (CVL), and (2) using a genetic algorithm
that finds at run-time nearly-optimal configurations using the information
provided by the variability model. We also specify a case study
and we use it to evaluate our approach, showing that it is efficient and
suitable for devices with scarce resources.Campus de Excelencia Internacional Andalucia Tech y proyectos de investigaciĂłn TIN2008-01942, P09-TIC-5231 and INTER-TRUST FP7-317731
Understanding user experience of mobile video: Framework, measurement, and optimization
Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study
Policy Enforcement with Proactive Libraries
Software libraries implement APIs that deliver reusable functionalities. To
correctly use these functionalities, software applications must satisfy certain
correctness policies, for instance policies about the order some API methods
can be invoked and about the values that can be used for the parameters. If
these policies are violated, applications may produce misbehaviors and failures
at runtime. Although this problem is general, applications that incorrectly use
API methods are more frequent in certain contexts. For instance, Android
provides a rich and rapidly evolving set of APIs that might be used incorrectly
by app developers who often implement and publish faulty apps in the
marketplaces. To mitigate this problem, we introduce the novel notion of
proactive library, which augments classic libraries with the capability of
proactively detecting and healing misuses at run- time. Proactive libraries
blend libraries with multiple proactive modules that collect data, check the
correctness policies of the libraries, and heal executions as soon as the
violation of a correctness policy is detected. The proactive modules can be
activated or deactivated at runtime by the users and can be implemented without
requiring any change to the original library and any knowledge about the
applications that may use the library. We evaluated proactive libraries in the
context of the Android ecosystem. Results show that proactive libraries can
automati- cally overcome several problems related to bad resource usage at the
cost of a small overhead.Comment: O. Riganelli, D. Micucci and L. Mariani, "Policy Enforcement with
Proactive Libraries" 2017 IEEE/ACM 12th International Symposium on Software
Engineering for Adaptive and Self-Managing Systems (SEAMS), Buenos Aires,
Argentina, 2017, pp. 182-19
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