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Artificial Intelligence (AI) applications based on Deep Neural Networks (DNN) or Deep Learning (DL) have become popular due to their success in solving problems likeimage analysis and speech recognition.

Deep Leaning and code embedding based approach to linguistic detecting anti-patterns in Infrastructure as code. This is from SODALITE smell and defect prediction task.

Deep Leaning and code embedding based approach to linguistic detecting anti-patterns in Infrastructure as code. This is from SODALITE smell and defect prediction task.

This document provides a wide view of the extent of communication and dissemination strategy of SODALITE, during 36 months of the project duration.

The SODALITE architecture is divided into 3 main layers: Modelling layer, Infrastructure as Code layer, and Runtime layer. This document summarizes the available stable components in each of these layers, and points to instructions on how these components can be accessed and built.

This deliverable reports on the development status after M12 of the SODALITE Runtime Layer and the integration of its components with the rest of the SODALITE platform.

This deliverable presents the status of development of the Infrastructure as Code (IaC) layer within the SODALITE platform, as well as the integration with other components and tools in SODALITE platform at the end of the first year of the project. 

The present deliverable reports on the work carried out within T3.1 “Application Semantic Modelling” and T3.2 “Infrastructure Semantic Modelling”, relevant to the development of the SODALITE ontologies (abstraction layer) and the representation and mapping of cloud applications and infrastructures to ontological entities.

This document sets some rules and guidelines on how contributors can support the development of the SODALITE platform, how the SODALITE software is organized in various related open source repositories, and the practical procedures to be used to propose changes and to see them accepted by the SODALITE team.

Journal of 2020 IEEE International Conference on Software Architecture (ICSA)

pp. 103-113

10th International Conference on Web Intelligence, Mining and Semantics (WIMS)

IIn this deliverable, we report on our key contributions towards the implementation and evaluation of the SODALITE platform and use cases. Whereas Deliverable D6.1 paved the way in M6 for the SODALITE platform by detailing the overall implementation plan and roadmap, we now report on the current status of implementation up to M12.

This deliverable presents the time plan for the development of the SODALITE platform, as well as the implementation plan of the project´s use cases.

In this deliverable, we report on our key contributions towards the implementation and evaluation of the SODALITE platform and use cases. Whereas Deliverable D6.1 paved the way in M6 for the SODALITE platform by detailing the overall implementation plan and roadmap, we now report on the current status of implementation up to M12.

This deliverable presents the time plan for the development of the SODALITE platform, as well as the implementation plan of the project’s use cases.

This deliverable reports on the progress of the SODALITE project in developing a model for application and infrastructure performance.

The UML use cases and the architecture presented in this deliverable have been defined with the contribution of all partners in the project and constitute the main guidelines that will steer the work in the technical work packages during the first iteration in the project.

Journal of Software: Practice and Experience

Volume49, Issue5, May 2019

Pages 813-839

2019 IEEE International Conference on Services Computing (SCC) in Milan (Italy)

2019 IEEE International Congress on Big Data (BigDataCongress) in Milan (Italy).

IEEE International Conference on Cloud Networking, 4-6 November 2019 in Coimbra (Portugal).

2019 IEEE International Congress on Big Data (BigDataCongress), pp. 85-92. IEEE, 2019 in Milan (Italy).