Abstract

Abstract
This paper presents GLITCH, a new technology-agnostic framework that enables automated polyglot code smell detection for Infrastructure as Code scripts. GLITCH uses an intermediate representation on which different code smell detectors can be defined. It currently supports the detection of nine security smells and nine design & implementation smells in scripts written in Ansible, Chef, Docker, Puppet, or Terraform. Studies conducted with GLITCH not only show that GLITCH can reduce the effort of writing code smell analyses for multiple IaC technologies, but also that it has higher precision and recall than current state-of-the-art tools. A video describing and demonstrating GLITCH is available at: https://youtu.be/E4RhCcZjWbk.

Abstract
Cities worldwide have agreed on ambitious goals regarding carbon neutrality; thus, smart cities face challenges regarding active and shared mobility due to public transportation's low attractiveness and lack of real-time multimodal information. These issues have led to a lack of data on the community's mobility choices, traffic commuters' carbon footprint and corresponding low motivation to change habits. Besides, many consumers are reluctant to use some software tools due to the lack of data privacy guarantee. This paper presents a methodology developed in the FranchetAI project that addrebes these issues by providing distributed privacy-preserving machine learning models that identify travel behaviour patterns and respective GHG emissions to recommend alternative options. Also, the paper presents the developed FranchetAI mobile prototype. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Abstract
The Software-Defined Storage (SDS) paradigm has emerged as a way to ease the orchestration and management complexities of storage systems. This work aims to mitigate the storage performance issues that large-scale HPC infrastructures are currently facing by developing a scalable and dependable control plane that can be integrated into an SDS design to take full advantage of the tools this paradigm offers. The proposed solution will enable system administrators to define storage policies (e.g., I/O prioritization, rate limiting) and, based on them, the control plane will orchestrate the storage system to provide better QoS for data-centric applications.

Abstract

Abstract