Our project’s official White Paper ‘From zero to Serverless: The RADON approach’ is officially published!
Satish Narayana Srirama, Mainak Adhikari, and Souvik Paul propose a new container-aware application scheduling strategy with an auto-scaling policy.
Stefano Dalla Palma, Dario Di Nucci, and Damian A. Tamburri present AnsibleMetrics, a Python-based static source code measurement tool to characterize Infrastructure-as-Code.
In this paper, Stefano Dalla Palma, Dario Di Nucci, Fabio Palomba, and Damian Andrew Tamburri, propose a catalog consisting of 46 metrics to identify IaC properties focusing on Ansible, one of the most popular IaC language to date, and shows how they can be used to analyze IaC scripts.
14 May: Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics
In this paper, published in IEEE Transactions on Software Engineering, S. Dalla Palma, D. Di Nucci, F. Palomba, and D. A. Tamburri propose a fully integrated machine-learning framework for IaC Defect Prediction, that allows for repository crawling, metrics collection, model building, and evaluation.
In the paper ‘Quality-Aware DevOps Research: Where Do We Stand?’, A. Alnafessah, A. U. Gias, R. Wang, L. Zhu, G. Casale, and A. Filieri, address this gap by comprehensively surveying existing efforts in this area, categorizing them according to the stage of the DevOps lifecycle to which they primarily contribute.
Together with QORE Lab, we are organising on May 17th, 16:00 – 17:30 EEST, a free workshop on how to deploy and orchestrate serverless applications in the cloud using open source tools!
Earlier this month, we had the amazing opportunity to join this year’s 12th ACM/SPEC International Conference of Performance Engineering ( ICPE 2021)!
This deliverable Deliverable 5.3 ‘Technology Library’ introduces the technology library core concepts for handling the reusable content in DevOps and the necessary abstractions defined in the RADON project and designed according to the user requirements.
The RADON team presents the second iteration of the RADON modeling profile that focuses on the representation of serverless application topologies and data flows using a set of abstract and concrete modeling constructs defined using the TOSCA cloud modeling language.
Our project’s official White Paper ‘From zero to Serverless: The RADON approach’ is officially published!
Satish Narayana Srirama, Mainak Adhikari, and Souvik Paul propose a new container-aware application scheduling strategy with an auto-scaling policy.
Stefano Dalla Palma, Dario Di Nucci, and Damian A. Tamburri present AnsibleMetrics, a Python-based static source code measurement tool to characterize Infrastructure-as-Code.
In this paper, Stefano Dalla Palma, Dario Di Nucci, Fabio Palomba, and Damian Andrew Tamburri, propose a catalog consisting of 46 metrics to identify IaC properties focusing on Ansible, one of the most popular IaC language to date, and shows how they can be used to analyze IaC scripts.
14 May: Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics
In this paper, published in IEEE Transactions on Software Engineering, S. Dalla Palma, D. Di Nucci, F. Palomba, and D. A. Tamburri propose a fully integrated machine-learning framework for IaC Defect Prediction, that allows for repository crawling, metrics collection, model building, and evaluation.
In the paper ‘Quality-Aware DevOps Research: Where Do We Stand?’, A. Alnafessah, A. U. Gias, R. Wang, L. Zhu, G. Casale, and A. Filieri, address this gap by comprehensively surveying existing efforts in this area, categorizing them according to the stage of the DevOps lifecycle to which they primarily contribute.
This deliverable Deliverable 5.3 ‘Technology Library’ introduces the technology library core concepts for handling the reusable content in DevOps and the necessary abstractions defined in the RADON project and designed according to the user requirements.
The RADON team presents the second iteration of the RADON modeling profile that focuses on the representation of serverless application topologies and data flows using a set of abstract and concrete modeling constructs defined using the TOSCA cloud modeling language.
Our team presented a software defect prediction tool for IaC to help software practitioners in prioritizing their inspection efforts for IaC scripts.
As a part of the RADON framework, CTT will provide the functionality for defining, generating, executing, and refining continuous tests of application functions, data pipelines, and microservices, as well as for reporting test results.