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SYSTOR '21: Proceedings of the 14th ACM International Conference on Systems and Storage - June 2021 - Article No.: 23 - Pages 1

TSOS21: First workshop on trustworthy software and open source, March 23-25, 2021, Virtual Conference

SYSTOR '19: Proceedings of the 12th ACM International Conference on Systems and Storage - May 2019 - Pages 196

Abstract: 

European Conference on Software Architecture - ECSA 2020: Software Architecture pp 247-259

MaLTeSQuE 2019: Proceedings of the 3rd ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation - August 2019 - Pages 37–42

Journal of Grid Computing volume 19, Article number: 29 (2021) 

4th Special Session on High-Performance Services Computing and Internet Technologies (@HPCS2020)

2020 IEEE International Conference on Web Services (ICWS)

Journal Information and Software Technology Volume 127, November 2020, 106376

ScienceDirect - Information and Software Technology Volume 137, September 2021, 106593

ACM Transactions on Software Engineering and MethodologyVolume 30Issue

1 January 2021 Article No.: 1pp 1–30 

Sensors 2020, 20(9), 2464; https://doi.org/10.3390/s20092464

ESOCC 2020: Advances in Service-Oriented and Cloud Computing pp 173-178

The Vehicle IoT use case builds on ADTP’s KnowGo Car data management and services platform for connected vehicles.

In this deliverable, we report on the implementation progress in the second year of the project, its culmination in the second prototype of the SODALITE platform, and the evaluation of the release through a combination of technical KPI assessment and validation by the project’s three demonstratin

The SODALITE Framework is the software system that includes all SODALITE stable components. This deliverable includes the description of the software that makes up the SODALITE stack, while the actual software is available through the GitHub SODALITE repository (https://github.com/SODALITE-EU).

This deliverable reports on the status of the development, at M24, of the SODALITE Runtime Layer and the integration of its components with the rest of the SODALITE platform. This is the second of three deliverables in this series, to be released annually during the project lifetime.

The purpose of this deliverable is to present the status of the IaC Management Layer at the end of the second year of the SODALITE project.

This deliverable is the continuation of deliverable D2.1 and provides the consolidated evolution of requirements, KPIs, evaluation plan and architecture over the second year.

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.