MADES FP7 EU project: Effective high level SysML/MARTE methodology for real-time and embedded avionics systems

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Reuse and Migration of Legacy Systems to Interoperable Cloud Services - The REMICS project

International audienc

Analysis of Development Tool Usage in Software Engineering Classes

In this paper, the survey, dedicated to the usage of software systems in a software development process, is analysed. The survey was conducted among the students of Innopolis University. Based on the result of the survey, the following conclusions were made: (1) Windows, macOS and Linux-based operating systems have almost equal share of usage among future software developers (2) the most popular IDE is IntelliJ IDEA, however, to the end of the studying process students the diversity of IDEs usage increases (3) the mostly used code management system by far is Github, with almost 100% share (4) Trello and Jira are the most popular project management software for lightweight and complex industrial projects respectively. The obtained results will be used for the prioritization of the development of integration agents for InnoMetrics project, as well as for the adaptation of a studying process in academic institutions to make it more relevant to the given trends and for the market analysis of software engineering environment

On study results: Round trip engineering of space systems

Software developed for the space domain often has to deal with extremely long mission times (sometimes in the order of 15 to 20 years). During the lifetime of a mission programming platforms evolve and sometimes disappear forcing migrations or updates. Migration can also be triggered by the appearance of new platforms that can improve scalability, performance. European Space Agency (ESA) is interested in modernization approaches that simplify platform migration and that preserve the business values of systems. The Architecture Driven Modernization (ADM) promoted by the Object Management Group (OMG) proposes to recover the models which represent the business value and proceed with the platform migration in a forward MDA process. This article provides results of a study dedicated to assess the state-of-the-art tools and methods for model driven platform migration, including model-based testing and metrication

REMICS- REuse and migration of legacy applications to interoperable cloud services

The main objective of the REMICS project is to specify, develop and evaluate a tool-supported model-driven methodology for migrating legacy applications to interoperable service cloud platforms. The migration process consists of understanding the legacy system in terms of its architecture and functions, designing a new SOA application that provides the same or better functionality, and verifying and implementing the new application in the cloud. The demonstrations will cover the following REMICS research topics: model-based analysis and testing and model-driven interoperability with the tools by Fraunhofer FOKUS and SINTEF. Video is published at http://goo.gl/ExV38

AIDOaRt: AI-augmented Automation for DevOps, a model-based framework for continuous development in Cyber-Physical Systems

The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modeling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will (1) enable the dynamic observation and analysis of system data collected at both runtime and design time and (2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans

Metrics for Software Process Quality Assessment in the Late Phases of SDLC

The software systems worldwide increase in a density on a daily basis. The success in nowadays competitive market requires sustainable and quality software product. Controversially to the quantity of software products, the quality and cost of the software are tend to depend on several aspects. However, they are not fully inculcated yet as a fundamentally essential. The full control over the software quality requires software metrics to be introduced. By effective usage of software quality metrics one can monitor the software development process, minimize the cost, track the resource usage and maintain the expected results. This paper reviews the late phases and the existing software quality models to track software process quality metrics in these late phases. And based on the summarized studies we describe our system architecture in the way to evaluate the software quality with embedded external systems. This paper find outs additional metrics we can measure with the help of our framework