Software Engineering

Spirals team

Self adaptation for distributed services and large software systems

Leader: Lionel Seinturier

PRESENTATION MEMBERS THESES PUBLICATIONS

Presentation

Spirals is conducting research activities in the domains of distributed systems and software sciences. Spirals aims at introducing more automation in the adaptation mechanisms of software systems, in particular, transitioning from adaptive systems to self-adaptive systems. Spirals targets especially two properties: self-healing and self-optimization.
With self-healing, Spirals aims at studying and tailoring data mining and machine learning solutions for the design and implementation of software systems. This contributes to the goal of obtaining solutions for automatic software repair.
With self-optimization, Spirals aims at sharing, collecting and analyzing distributed behaviors and data to continuously tailor, optimize and keep under working conditions software systems. This participates to the goal of obtaining eternal distributed systems.

Zeinab Abou khalil

Exploring the variability and evolution of cloud computing systems

Mohamed chakib Belgaid

Développement durable des logiciels vers une optimisation énergétique de bout en bout des systèmes logiciels

Sacha Brisset

Automatic Spotting and fixing or Recurrent user Experience issues. Detecting and Fixing Anomalies by applying Machine Learning on user Experience Data

Antonin Durey

Leveraging Browser Fingerprinting to Fitht Fraud on the Web

Guillaume Fieni

GreenData : vers un traitement efficient et éco-responsable des grandes masses de données numériques

Trinh Le Khanh

Conception d'applications cloud auto-adaptatvess correctes par construction à l'aide de méthodes formelles

Vikas Mishra

Collaborative Strategies to protect against browser fingerprinting

Zakaria Ournani

Eco-conception des logiciels : modélisation de l'efficience énergétique des logiciels et conception d'outils pour mesurer et réduire leur consommation d'énergie

Marion Tommasi

Collaborative Data-centric Workflows : Towards Knowledge Centric Workflows and Integrating Uncertain Data

Les autres équipes du groupe thématique ' GL '

CARAMEL CARBON RMoD