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Abstract-The accelerating progress of network speed, reliability and security creates an increasing demand to move software and services from being stored and processed locally on users' machines to being managed by third parties that are accessible through the network. This has created the need to develop new software development methods and software architectural styles that meet these new demands. One such example in software architectural design is the recent emergence of the microservices architecture to address the maintenance and scalability demands of online service providers. As microservice architecture is a new research area, the need for a systematic mapping study is crucial in order to summarise the progress so far and identify the gaps and requirements for future studies. In this paper we present a systematic mapping study of microservices architectures and their implementation. Our study focuses on identifying architectural challenges, the architectural diagrams/views and quality attributes related to microsevice systems.

DATR is a declarative language for representing a restricted class of inheritance networks, permitting both multiple and default inheritance. The principal intended area of application is the representation of lexical entries for natural language processing, and we use examples from this domain throughout. In this paper we present the syntax and inference mechanisms for the language. The goal of the DATR enterprise is the design of a simple language that (i) has the necessary expressive power to encode the lexical entries presupposed by contemporary work in the unification grammar tradition, (ii) can express all the evident generalizations about such entries, (iii) has an explicit theory of inference, (iv) is computationally tractable, and (v) has an explicit declarative semantics. The present paper is primarily concerned with (iii), though the examples used may hint at our strategy in respect of (i) and (ii).

Information available to the public influences the approach of the population toward vaccination against influenza compared with other preventative approaches. In this study, we have analyzed the first 200 websites returned by searching Google on two topics (prevention of influenza and influenza vaccine), in English and Italian. For all the four searches above, websites were classified according to their typology (government, commercial, professional, portals, etc.) and for their trustworthiness as defined by the Journal of the American Medical Association (JAMA) score, which assesses whether they provide some basic elements of information quality (IQ): authorship, currency, disclosure, and references. The type of information described was also assessed to add another dimension of IQ. Websites on influenza prevention were classified according to the type of preventative approach mentioned (vaccine, lifestyle, hygiene, complementary medicine, etc.), whether the approaches were in agreement with evidence-based medicine (EBM) or not. Websites on influenza vaccination were classified as pro- or anti-vaccine, or neutral. The great majority of websites described EBM approaches to influenza prevention and had a pro-vaccine orientation. Government websites mainly pointed at EBM preventative approaches and had a pro-vaccine orientation, while there was a higher proportion of commercial websites among those which promote non-EBM approaches. Although the JAMA score was lower in commercial websites, it did not correlate with the preventative approaches suggested or the orientation toward vaccines. For each of the four search engine result pages (SERP), only one website displayed the health-of-the-net (HON) seal. In the SERP on vaccines, journalistic websites were the most abundant category and ranked higher than average in both languages. Analysis using natural language processing showed that journalistic websites were mostly reporting news about two specific topics (different in the two languages). While the ranking by Google favors EBM approaches and, in English, does not promote commercial websites, in both languages it gives a great advantage to news. Thus, the type of news published during the influenza season probably has a key importance in orienting the public opinion due to its high visibility. This raises important questions on the relationships between health IQ, trustworthiness, and newsworthiness.

We present the rags (Reference Architecture for Generation Systems) framework: a specification of an abstract Natural Language Generation (NLG) system architecture to support sharing, re-use, comparison and evaluation of NLG technologies. We argue that the evidence from a survey of actual NLG systems calls for a different emphasis in a reference proposal from that seen in similar initiatives in information extraction and multimedia interfaces. We introduce the framework itself, in particular the two-level data model that allows us to support the complex data requirements of NLG systems in a flexible and coherent fashion, and describe our efforts to validate the framework through a range of implementations.