System Analysis and Robustness

Eugenio Moggi, Amin Farjudian, Walid Taha

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

2 Citations (Scopus)

Abstract

Software is increasingly embedded in a variety of physical contexts. This imposes new requirements on tools that support the design and analysis of systems. For instance, modeling embedded and cyber-physical systems needs to blend discrete mathematics, which is suitable for modeling digital components, with continuous mathematics, used for modeling physical components. This blending of continuous and discrete creates challenges that are absent when the discrete or the continuous setting are considered in isolation. We consider robustness, that is, the ability of an analysis of a model to cope with small amounts of imprecision in the model. Formally, we identify analyses with monotonic maps between complete lattices (a mathematical framework used for abstract interpretation and static analysis) and define robustness for monotonic maps between complete lattices of closed subsets of a metric space.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages36-44
Number of pages9
DOIs
Publication statusPublished - 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11200 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Analyses
  • Domain theory
  • Robustness

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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