3 citations · 9 across the 17 of their papers we have counts for
9 papers · 1 filter
Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification
Simos Gerasimou, Xingyu Zhao
Combining Bayesian learning and quantitative verification is a powerful toolset for analysing key quantitative properties of software systems, like reliability and response time. H…
Tree-Based versus Hybrid Graphical-Textual Model Editors: An Empirical Study of Testing Specifications
Ionut Predoaia, James Harbin, Simos Gerasimou +3
Tree-based model editors and hybrid graphical-textual model editors have advantages and limitations when editing domain models. Data is displayed hierarchically in tree-based model…
Fast Parametric Model Checking through Model Fragmentation
Xinwei Fang, Radu Calinescu, Simos Gerasimou +1
Parametric model checking (PMC) computes algebraic formulae that express key non-functional properties of a system (reliability, performance, etc.) as rational functions of the sys…
Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning
Mirko D'Angelo, Sona Ghahremani, Simos Gerasimou +4
Engineering collective adaptive systems (CAS) with learning capabilities is a challenging task due to their multi-dimensional and complex design space. Data-driven approaches for C…
Supporting Robotic Software Migration Using Static Analysis and Model-Driven Engineering
Sophie Wood, Nicholas Matragkas, Dimitris Kolovos +2
The wide use of robotic systems contributed to developing robotic software highly coupled to the hardware platform running the robotic system. Due to increased maintenance cost or…
Genetic Improvement @ ICSE 2020
William B. Langdon, Westley Weimer, Justyna Petke +13
Following Prof. Mark Harman of Facebook's keynote and formal presentations (which are recorded in the proceedings) there was a wide ranging discussion at the eighth international G…