Model Based Development of Quality-Aware Software Services

Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

Incremental Common Criteria certification processes using DevSecOps practices

The growing digitalisation of our economies and societies is driving the need for increased connectivity of critical applications and infrastructures to the point where failures can lead to important disruptions and consequences to our lives. One growing source of failures for critical applications and infrastructures originates from cybersecurity threats and vulnerabilities that can be exploited in attacks. One approach to mitigating these risks is verifying that critical applications and infrastructures are sufficiently protected by certification of products and services. However, reaching sufficient assurance levels for product certification may require detailed evaluation of product properties. An important challenge for product certification is dealing with product evolution: now that critical applications and infras- tructures are connected they are being updated on a more frequent basis. To ensure continuity of certification, updates must be analysed to verify the impact on certified cybersecurity properties. Impacted properties need to be re-certified. This paper proposes a lightweight and flexible incremental certification process that can be integrated with DevSecOps practices to automate as much as possible evidence gathering and certification activities. The approach is illustrated on the Common Criteria product certification scheme and a firewall update on an automotive case study. Only the impact analysis phase of the incremental certification process is illustrated

BEACON: A Cloud Network Federation Framework

This paper presents the BEACON Framework, which will enable the provision and management of cross-site virtual networks for federated cloud infrastructures in order to support the automated deployment of applications and services across different clouds and datacenters. The proposed framework will support different federation architectures, going from tightly coupled (datacenter federation) to loosely coupled (cloud federation and multi-cloud orchestration) architectures, and will enable the creation of Layer 2 and Layer 3 overlay networks to interconnect remote resources located at different cloud sites. A high level description of the main components of the BEACON framework is also introduced

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer, studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory, a versatile observatory designed to address the Hot and Energetic Universe science theme, selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), it aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over an hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR, browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters. Finally we briefly discuss on the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, and touch on communication and outreach activities, the consortium organisation, and finally on the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. (abridged).Comment: 48 pages, 29 figures, Accepted for publication in Experimental Astronomy with minor editin

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory. Athena is a versatile observatory designed to address the Hot and Energetic Universe science theme, as selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), X-IFU aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over a hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR (i.e. in the course of its preliminary definition phase, so-called B1), browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters, such as the instrument efficiency, spectral resolution, energy scale knowledge, count rate capability, non X-ray background and target of opportunity efficiency. Finally, we briefly discuss the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, touch on communication and outreach activities, the consortium organisation and the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. The X-IFU will be provided by an international consortium led by France, The Netherlands and Italy, with ESA member state contributions from Belgium, Czech Republic, Finland, Germany, Poland, Spain, Switzerland, with additional contributions from the United States and Japan.The French contribution to X-IFU is funded by CNES, CNRS and CEA. This work has been also supported by ASI (Italian Space Agency) through the Contract 2019-27-HH.0, and by the ESA (European Space Agency) Core Technology Program (CTP) Contract No. 4000114932/15/NL/BW and the AREMBES - ESA CTP No.4000116655/16/NL/BW. This publication is part of grant RTI2018-096686-B-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This publication is part of grant RTI2018-096686-B-C21 and PID2020-115325GB-C31 funded by MCIN/AEI/10.13039/501100011033

Analogical reuse of requirements frameworks

Reusing similar requirements fragments is among the promising ways to reduce elaboration time and increase requirements quality. This paper investigates the application of analogical reasoning techniques to complete partial requirements specifications. A case base is assumed to be available; it contains requirements frameworks involving goals, constraints, objects, actions, and agents from systems already specified. We show how a rich requirements meta-model coupled with an expressive formal assertion language may increase the effectiveness of analogical reuse. An acquisition problem is first specified by the requirements engineer as a query formulated in the vocabulary of the specification fragments built so far. Source cases and partial mappings are found by query generalization followed by search through the case base. Once analogies have been confirmed, mappings are completed by use of relevance rules that distinguish in the formal assertions what is relevant to the analogy from what is irrelevant. Best analogies are then selected and extended in such a way that logical properties of the answers to the query may be verified, thus increasing confidence in the analogy. The approach is illustrated by analogical acquisition of specifications of a meeting scheduler in the KAOS goal-oriented specification language

Making seasonal outlooks of Arctic sea ice and Atlantic hurricanes valuable —not just skillful

© Copyright [19-02-2020] American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (http://www.copyright.com). Questions about permission to use materials for which AMS holds the copyright can also be directed to [email protected]. Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (http://www.ametsoc.org/CopyrightInformation).In recent years, a big effort has been made by part of the climate community toward the development of climate services in order to make climate information decision oriented. In a climate forecasting context, this means identifying climate variables, thresholds and/or events of relevance to users. Once identified, these elements, which generally do not coincide with variables typically forecasted by the scientific community, are analyzed to determine whether they can be predicted both reliably and skillfully at the appropriate time scale. This process generally requires a sustained dialogue between the different parties involved before coming to a fruitful conclusion. Here, we discuss two such efforts that attempt to bridge the gap between climate forecasting and application for two phenomena already receiving a fair amount of attention from the general public: hurricanes and Arctic sea ice.We would like to acknowledge the participation of the numerous forecasting organizations that submit their forecasts to both platforms on a regular basis, without whose support neither projects would be possible. LPC and PJK would like to acknowledge the support of XL Catlin (now AXA XL). FM is a F.R.S.–FNRS Research Associate. PJK would also like to acknowledge support from the G. Unger Vetlesen Foundation. JS acknowledges the support of NE/R017123/1 [NSFGEO-NERC Advancing Predictability of Sea Ice: Phase 2 of the Sea Ice Prediction Network (SIPN2)]. Finally, we are grateful to three anonymous reviewers who provided us with helpful comments.Peer Reviewe