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

Incorporating Agile with MDA Case Study: Online Polling System

Nowadays agile software development is used in greater extend but for small organizations only, whereas MDA is suitable for large organizations but yet not standardized. In this paper the pros and cons of Model Driven Architecture (MDA) and Extreme programming have been discussed. As both of them have some limitations and cannot be used in both large scale and small scale organizations a new architecture has been proposed. In this model it is tried to opt the advantages and important values to overcome the limitations of both the software development procedures. In support to the proposed architecture the implementation of it on Online Polling System has been discussed and all the phases of software development have been explained.Comment: 14 pages,1 Figure,1 Tabl

Genetic parameter estimates for plasma oxidative status traits in slaughter pigs

The aim of the present study was to assess the effect of sex and to estimate genetic parameters for several traits related to plasma oxidative status in slaughter pigs, i.e., ferric reducing ability of plasma (FRAP), concentrations of a-tocopherol and malondialdehyde (MDA), and glutathione peroxidase (GPx) activity. Blood samples were collected at slaughter from 477 Pietrain x (Landrace x Large White intercross) pigs of 2 performance test stations. Heritabilities (+/- SE) of plasma oxidative status traits as well as their phenotypic and additive genetic correlations with animal performance traits were estimated with multiple-trait REML animal models using VCE software. Results displayed no significant difference between barrows and gilts for FRAP and alpha-tocopherol in plasma. However, gilts had a significantly higher concentration of MDA and lower GPx activity compared with barrows. Heritability estimates were high for GPx (0.55 +/- 0.05), and medium to low for alpha-tocopherol (0.30 +/- 0.06), FRAP (0.22 +/- 0.05), and MDA (0.15 +/- 0.04). Estimated additive genetic and phenotypic correlations between these four traits were generally low, except for a negative additive genetic correlation between FRAP and GPx of -0.45 (+/- 0.23). Additive genetic correlations between plasma oxidative status traits and animal performance traits were also generally absent or low with maximum values of similar to 0.3. Parameter estimates in this study have to be interpreted with caution because of the small size of the dataset. Nevertheless, it may be concluded that there is considerable additive genetic variance for plasma oxidative status traits in slaughter pigs. More research is warranted on the genetic determination of oxidative stress in farm animals and its relevance in breeding programs

Semantic model-driven development of service-centric software architectures

Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology