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Grant
Agency: European Commission | Branch: FP7 | Program: JTI-CP-ARTEMIS | Phase: SP1-JTI-ARTEMIS-2010-4;SP1-JTI-ARTEMIS-2010-1 | Award Amount: 7.76M | Year: 2011

The PRESTO project aims at improving test-based embedded systems development and validation, while considering the constraints of industrial development processes. This project is based on the integration of (a) test traces exploitation (generated by test execution in the software integration phase induced by the industrial development process, to validate the requirements of the system) along with (b) platform models and (c) design space exploration techniques. The expected result of the project is to enable functional and performance analysis and platform optimisation at early stage of the design development. The approach of PRESTO is to model the software/hardware allocation, by the use of a modelling framework based on the UML profile for model-driven development of Real Time and Embedded Systems (MARTE). The analysis tools, among them timing analysis including Worst Case Execution Time (WCET) analysis, scheduling analysis and possibly more abstract system-level timing analysis techniques will receive as inputs on the one hand information from the MARTE performance modelling of the HW/SW-platform, and on the other hand behavioural information of the software design from tests results of the integration test execution. Of particular novelty in PRESTO is the exploitation of traces for the exclusion of over-pessimistic assumptions during timing analysis: instead of taking all possible inputs and states into account for a worst-case analysis, a set of relevant traces is analyzed separately to reduce the set of possible inputs and states for each trace. A particular attention will be given to industrial development constraints, which means 1) as little cost as possible in term of extra specification time and need of expertise, 2) a simple use of the tools, 3) a smooth integration in the current design process, 4) a tool framework flexible enough to be adapted to different process methodologies, design languages and integration test frameworks, 5) analysis results DoW (TA) Approved by the ARTEMIS JU on 26/05/2014


Grant
Agency: European Commission | Branch: H2020 | Program: IA | Phase: ICT-15-2016-2017 | Award Amount: 16.19M | Year: 2017

The data intensive target sector selected for the DataBio project is the Data-Driven Bioeconomy, focusing in production of best possible raw materials from agriculture, forestry and fishery/aquaculture for the bioeconomy industry to produce food, energy and biomaterials taking into account also various responsibility and sustainability issues. DataBio proposes to deploy a state of the art, big data platform on top of the existing partners infrastructure and solutions - the Big DATABIO Platform.The work will be continuous cooperation of experts from end user and technology provider companies, from bioeconomy and technology research institutes, and of other partners. In the pilots also associated partners and other stakeholders will be actively involved. The selected pilots and concepts will be transformed to pilot implementations utilizing co-innovative methods and tools where the bioeconomy sector end user experts and other stakeholders will give input to the user and sector domain understanding for the requirements specifications for ICT, Big Data and Earth Observation experts and for other solution providers in the consortium. Based on the preparation and requirement specifications work the pilots are implemented utilizing and selecting the best suitable market ready or almost market ready Big Data and Earth Observation methods, technologies, tools and services to be integrated to the common Big DATABIO Platform. During the pilots the close cooperation continues and feedback from the bioeconomy sector user companies will be utilized in the technical and methodological upgrades to pilot implementations. Based on the pilot results and the new solutions also new business opportunities are expected. In addition during the pilots the end user utilizers are participating trainings to learn how to use the solutions and developers also outside the consortium will be activated in the Hackathons to design and develop new tools, services and application for the platform.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-10-2016 | Award Amount: 5.00M | Year: 2016

Context. Software quality is an essential competitive factor for the success of IT companies nowadays. Recent technological breakthroughs such as cloud technologies, the emergence of IoT and technologies such as 5G, pose demanding quality challenges in software development. Problem. Optimal software quality asks for the appropriate integration of quality requirements (QRs) in the software life-cycle.However, software development methodologies still provide limited support to QR management which is utterly important in rapid software development processes (RSDP): faster and more frequent release cycles should not compromise software quality. Concept. Q-Rapids defines an empirical-based, data-driven quality-aware rapid software development methodology. QRs are incrementally elicited and refined based on data gathered both during development and at runtime. This data is elaborated into quality-related key indicators presented to decision makers through a strategic dashboard with advanced capabilities. Selected QRs are integrated with functional requirements for their unified treatment in the RSDP. Outcome. A TRL7 validated Q-Rapids framework, including cutting-edge tools and methods to smartly manage QRs along with functional requirements in a similar rapid and holistic manner. Impact. Increase of software quality levels through continuous data gathering and analysis. Significant productivity increase to the software life-cycle by means of smooth and tool-supported integration of QRs in the RSDP. Shorter time to market due to reduction of quality-related maintenance efforts and more informed decision making in the planning of release cycles. Impact will be measured through 11 project indicators with defined target values. Consortium. 3 research organisations,1 SME, 2 mid-caps and 1 corporative with balanced geographical distribution. The consortium combines long research tradition in software development and cutting-edge technological knowhow in versatile ICT sectors


Grant
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2013.1.2 | Award Amount: 3.73M | Year: 2013

As Model Driven Engineering (MDE) is increasingly applied to larger and more complex systems, the current generation of modelling and model management technologies are being pushed to their limits in terms of capacity and efficiency, and as such, additional research is imperative in order to enable MDE to remain relevant with industrial practice and continue delivering its widely recognised productivity, quality, and maintainability benefits. The aim of MONDO is to tackle the increasingly important challenge of scalability in MDE in a comprehensive manner.\n\nAchieving scalability in modelling and MDE involves being able to construct large models and domain specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in a collaborative manner, advancing the state-of-the-art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for efficient storage, indexing and retrieval of large models. To address these challenges, MONDO brings together partners with a long track record in performing internationally-leading research on software modelling and MDE, and delivering research results in the form of robust, widely-used and sustainable open-source software, with industrial partners active in the fields of reverse engineering and systems integration, and a global consortium including more than 400 organisations from all sectors of IT.


Grant
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2011.1.2 | Award Amount: 9.00M | Year: 2012

Current Clouds offer is becoming day by day wider providing a vibrant technical environment, where SMEs can create innovative solutions and evolve their services. Cloud promises cheap and flexible services to end-users at a much larger scale than before. However, Cloud business models and technologies are still in their initial hype and characterized by critical early stage issues, which pose specific challenges and require advanced software engineering methods.\nThe main goal of MODAClouds is to provide methods, a decision support system, an open source IDE and run-time environment for the high-level design, early prototyping, semi-automatic code generation, and automatic deployment of applications on multi-Clouds with guaranteed QoS.\nModel-driven development combined with novel model-driven risk analysis and quality prediction will enable developers to specify Cloud-provider independent models enriched with quality parameters, implement these, perform quality prediction, monitor applications at run-time and optimize them based on the feedback, thus filling the gap between design and run-time. Additionally, MODAClouds provides techniques for data mapping and synchronization among multiple Clouds.\nMODAClouds innovations thus are: (i)simplify Cloud provider selection favoring the emergence of European Clouds, (ii) avoid vendor lock-in problems supporting the development of Cloud enabled Future Internet applications, (iii) provide quality assurance during the application life-cycle and support migration from Cloud to Cloud when needed.\nThe research is multi-disciplinary and will be grounded on expertise from several research areas. MODAClouds consortium consists of highly recognized Universities and research institutions that will assure a sound scientific progress, SME partners providing expertise on modelling tools, and large companies that assure industry relevance. The MODAClouds approach and tools will be applied on four industrial cases from different domains.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-01-2014 | Award Amount: 7.96M | Year: 2015

The aim of the INTO-CPS project is to create an integrated tool chain for comprehensive model-based design of Cyber-Physical Systems (CPSs). The tool chain will support the multidisciplinary, collaborative modelling of CPSs from requirements, through design, down to realisation in hardware and software. This will enable traceability at all stages of the development. INTO-CPS will support the holistic modelling of CPSs, allowing system models to be built and analysed that would otherwise not be possible using standalone tools. We will integrate existing industry-strength tools with high Technology Readiness Levels (TRL 69) in their application domains. The solution will be based centrally around Functional Mockup Interface (FMI)-compatible co-simulation. The project focuses on the pragmatic integration of these tools, making extensions in areas where a need has been recognised. The tool chain will be underpinned by a well-founded semantic foundations that ensures the results of analysis can be trusted. The tool chain will provide powerful analysis techniques for CPSs, including connection to SysML; generation and static checking of FMI interfaces; model checking; Hardware-in-the-Loop (HiL) and Software-in-the-Loop (SiL) simulation, supported by code generation. The tool chain will allow for both Test Automation (TA) and Design Space Exploration (DSE) of CPSs. The INTO-CPS technologies will be accompanied by a comprehensive set of method guidelines that describe how to adopt the INTO-CPS approach, lowering entry barriers for CPS development. The tool chain will be tested with case studies in railways, agriculture, building and automotive. The consortium has 4 academic and 7 industrial partners. The industrial partners comprise both tool vendors and case study owners. The INTO-CPS technology will enable experimenting with design alternatives enabling radical innovation where the overall concept is right first time, even when hardware prototypes does not yet exists.


Grant
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2011.4.4 | Award Amount: 4.60M | Year: 2012

The efficient and real-time exploitation of large streaming data sources and stored data poses many questions regarding the underlying platform, including:1) Performance - how can the potential performance of the platform be exploited effectively by arbitrary applications;2) Guarantees - how can the platform support guarantees regarding processing streaming data sources and accessing stored data; and3) Scalability - how can scalable platforms and applications be built.The fundamental challenge addressed by the project is to enable application development using an industrial strength programming language that enables the necessary performance and performance guarantees required for real-time exploitation of large streaming data sources and stored data.The projects vision is to create a Java Platform that can support a range of high-performance Intelligent Information Management application domains that seek real-time processing of streaming data, or real-time access to stored data. This will be achieved by developing Java and UML modelling technologies to provide:1) Architectural Patterns - using predefined libraries and annotation technology to extend Java with new directives for exploiting streaming I/O and parallelism on high performance platforms;2) Virtual Machine Extensions - using class libraries to extend the JVM for scalable platforms;3) Java Acceleration - performance optimisation is achieved using Java JIT to Hardware (FPGA), especially to enable real-time processing of fast streaming data;4) Performance Guarantees - will be provided for common application real-time requirements; and5) Modelling - of persistence and real-time within UML / MARTE to enable effective development, code generation and capture of real-time system properties.The project will use financial and web streaming case studies from industrial partners to provide industrial data and data volumes, and to evaluate the developed technologies.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-01-2016 | Award Amount: 4.91M | Year: 2017

Cyber-Physical Systems (CPS) find applications in a number of large-scale, safety-critical domains e.g. transportation, smart cities, etc. While the increased CPS adoption has resulted in the maturation of solutions for CPS development, a single consistent science of system integration for CPS has not yet been consolidated. Therefore CPS development remains a complex and error-prone task, often requiring a collection of separate tools. Moreover, interactions amongst CPS might lead to new behaviors and emerging properties, often with unpredictable results. Rather than being an unwanted byproduct, these interactions can become an advantage if explicitly managed since early design stages. CPSwarm tackles this challenge by proposing a new science of system integration and tools to support engineering of CPS swarms. CPSwarm tools will ease development and integration of complex herds of heterogeneous CPS that collaborate based on local policies and that exhibit a collective behavior capable of solving complex, industrial-driven, real-world problems. The project defines a complete toolchain that enables the designer to: (a) set-up collaborative autonomous CPSs; (b) test the swarm performance with respect to the design goal; and (c) massively deploy solutions towards reconfigurable CPS devices. Model-centric design and predictive engineering are the pillars of the project, enabling definition, composition, verification and simulation of collaborative, autonomous CPS while accounting for various dynamics, constraints and for safety, performance and cost efficiency issues. CPSwarm pushes forward CPS engineering at a larger scale, with an expected significant reduction of development time and costs. Project results will be tested in real-world use cases in 3 different domains: swarms of Unmanned Aerial Vehicles and Rovers for safety and security purposes; autonomous driving for freight vehicles; and swarm of opportunistically collaborating smart bikes.


Grant
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2011.1.2 | Award Amount: 3.59M | Year: 2012

OSSMETER aims to extend the state-of-the-art in the field of automated analysis and measurement of open-source software (OSS), and develop a platform that will support decision makers in the process of discovering, comparing, assessing and monitoring the health, quality, impact and activity of open-source software. To achieve this OSSMETER will compute trustworthy quality indicators by performing advanced analysis and integration of information from diverse sources including the project metadata, source code repositories, communication channels, bug tracking systems of OSS projects. OSSMETER does not aim at building another OSS forge but instead at providing a metaplatform for analysing existing OSS projects that are developed in existing OSS forges and foundations such as SourceForge, Google Code, GitHub, Eclipse, Mozilla and Apache.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-10-2016 | Award Amount: 4.52M | Year: 2017

Recent reports state that the adoption of open-source software (OSS) helps, resulting in savings of about $60 billion per year to consumers. However, the use of OSS also comes at enormous cost: choosing among OSS projects and maintaining dependence on continuously changing software requires a large investment. Deciding if an OSS project meets the required standards for adoption is hard, and keeping up-to-date with an evolving project is even harder. It involves analysing code, documentation, online discussions, and issue trackers. There is too much information to process manually and it is common that uninformed decisions have to be made with detrimental effects. CROSSMINER remedies this by automatically extracting the required knowledge and injecting it into the IDE of the developers, at the time they need it to make their design decisions. This allows them to reduce their effort in knowledge acquisition and to increase the quality of their code. CROSSMINER uniquely combines advanced software project analyses with online monitoring in the IDE. The developer will be monitored to infer which information is timely, based on readily available knowledge stored earlier by a set of advanced offline deep analyses of related OSS projects. To achieve this timely and ambitious goal, CROSSMINER combines six end-user partners (in the domains of IoT, multi-sector IT services, API co-evolution, software analytics, software quality assurance, and OSS forges), along with R&D partners that have a long track-record in conducting cutting-edge research on large-scale software analytics, natural language processing, reverse engineering of software components, model-driven engineering, and delivering results in the form of widely-used, sustainable and industrial-strength OSS. The development of the CROSSMINER platform is guided by an advisory board of world-class experts and the dissemination of the project will be led by The Open Group.

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