FAACS @ ECSA 2020

• 14:00 - 14:10: Opening (chair: Ludovico Iovino and Stéphanie Challita)
• 14:10 - 15:00: Invited talk (chair: Alessio Bucaioni)
  • Patrizio Pelliccione (University of L'Aquila, Italy, and Chalmers | University of Gothenburg, Sweden): (Ab)using MDE for SA
• 15:00 - 15:10: Break
• 15:10 - 15:30: Regular session I (chair: Amleto Di Salle)
  • Matteo Camilli: Continuous Formal Verification of Microservice-based Process Flows
• 15:30 - 16:20: Invited talk (chair: Matteo Camilli)
  • Catia Trubiani (Gran Sasso Science Institute, Italy): Performance Learning for Uncertainty of Software Systems
• 16:20 - 16:30: Break
• 16:30 - 17:30: Regular session II (chair: Stéphanie Challita)
  • Markus Frank et al.: Defining a Formal Semantic for Parallel Patterns in the Palladio Component Model using Hierarchical Queuing Petri Nets
  • Elvinia Riccobene et al.: Model-based Simulation at Runtime with Abstract State Machines
  • Asfand Yar et al.: Merging Railway Standard Notations in a Formal DSL-based Framework
• 17:30 - 17:40: Conclusion and remarks (chair: Matteo Camilli)

• Markus Frank et al., Defining a Formal Semantic for Parallel Patterns in the Palladio Component Model using Hierarchical Queuing Petri Nets
• Elvinia Riccobene et al., Model-based Simulation at Runtime with Abstract State Machines
• Asfand Yar et al., Merging Railway Standard Notations in a Formal DSL-based Framework

Catia is Assistant Professor in Computer Science at the Gran Sasso Science Institute, L’Aquila (AQ), Italy. She received the Ph.D. in Computer Science at the University of L’Aquila with a dissertation on the automated generation of architectural feedback from software performance analysis results. Previously she worked at the Electronic Engineering Department of University of Rome "Tor Vergata" within the framework of the Simple Mobile Services EU FP7 project. Before joining the Gran Sasso Science Institute, she has been with various international research institutes like the Imperial College of London (UK) and the Karlsruhe Institute of Technology (Germany). Among various national and international projects in which she was involved, she is principal investigator of the GSSI unit for the MIUR-PRIN project SEDUCE (Young Line action). She was awarded by Microsoft Research for the DESPACE research project (market value: 40k USD). Her main research interests include the quantitative modelling and analysis of interacting heterogeneous distributed systems. She is especially interested in model-based performance analysis and feedback on software architectures, model-based refactoring by means of software performance antipatterns, and trade-off quality analysis and optimization of software systems.

Title: Performance Learning for Uncertainty of Software Systems

Abstract: Uncertainty is particularly critical in software performance engineering when it relates to the values of parameters such as workload, operational profile, and resource demand, because such parameters inevitably affect the overall system performance. Prior work focused on monitoring the performance characteristics of software systems while considering the influence of different design alternatives. The problem of incorporating uncertainty as a first-class concept in the software development process to identify performance issues is still challenging. This talk aims to discuss these limitations by presenting two ways of handling uncertainty: (i) the specification of a new class of performance models capturing how the different uncertainties underlying a software system affect its performance characteristics; (ii) the application of a new method for estimating the uncertainty propagation and supporting the prediction of performance indices of interest. Such quantitative evaluation helps software engineers to identify performance issues.