Continous Delivery toolkit
ENACT will deliver two enablers that aim at improving the continuous delivery of smart IoT systems, with a specific focus on (i) agile and continuous evolution and (ii) ensuring the proper design of the system before delivery. A particular attention will be given to support the testing of smart IoT systems and the gradual migration from the test to the operation environment.
Agile Operation Toolkit
ENACT will deliver three innovative enablers to significantly reduce the burden of managing and maintaining smart IoT systems. A specific attention will be given (i) to ensure the trustworthiness of such systems and (ii) to automate operation activities as much as possible.
ENACT will deliver a set of enablers addressing specific crosscutting trustworthiness concerns such as ensuring proper robustness, security and privacy of smart IoT systems.
Best paper awards at MODELS'2020
The ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems (MODELS), is the premier conference series for model-driven software and systems engineering, and is organized with support of ACM SIGSOFT and IEEE TCSE. MODELS is a premier venue for ENACT for several reasons: (i) many of our enablers are applying and sometims evolving model-based approaches, (ii) the integration between the ENACT enablers is model-driven, and (iii) last but not the least, we believe model-driven engineering is a technology for enabling DevOps, for instance allowing to abstract key concepts that can foster collaboration between Dev and Ops or enabling continuous evolution through the email@example.com approach.
For all these reasons we are glad to announce that our work on DivENACT our Fleet Management solution developed by SINTEF in collaboration with TellU has received the best paper award in the practice and innovation track at MODELS'2020!
DivENACT is our solution for effective and efficient support of software diversity among large scale of IoT fleet, from the automatic generation of diverse software on both the code and configuraiton level, to the runtime management of large fleet with diversity considered.