From Verification to Causality-Based Explications (Invited Talk)
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Invited › peer-review
Contributors
Abstract
In view of the growing complexity of modern software architectures, formal models are increasingly used to understand why a system works the way it does, opposed to simply verifying that it behaves as intended. This paper surveys approaches to formally explicate the observable behavior of reactive systems. We describe how Halpern and Pearl’s notion of actual causation inspired verification-oriented studies of cause-effect relationships in the evolution of a system. A second focus lies on applications of the Shapley value to responsibility ascriptions, aimed to measure the influence of an event on an observable effect. Finally, formal approaches to probabilistic causation are collected and connected, and their relevance to the understanding of probabilistic systems is discussed.
Details
Original language | English |
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Title of host publication | 48th International Colloquium on Automata, Languages, and Programming, ICALP 2021 |
Editors | Nikhil Bansal, Emanuela Merelli, James Worrell |
Publisher | Schloss Dagstuhl – Leibniz-Zentrum für Informatik |
Pages | 1:1–1:20 |
ISBN (print) | 978-3-95977-195-5 |
Publication status | Published - 2 Jul 2021 |
Peer-reviewed | Yes |
Publication series
Series | 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021) ; Vol. 198 |
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Volume | 198 |
ISSN | 1868-8969 |
Conference
Title | 48th International Colloquium on Automata, Languages, and Programming |
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Abbreviated title | ICALP 2021 |
Duration | 12 - 16 July 2021 |
Website | |
Degree of recognition | International event |
Location | online |
City | Glasgow |
Country | United Kingdom |
External IDs
ORCID | /0000-0002-5321-9343/work/142236687 |
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ORCID | /0000-0002-8490-1433/work/142246187 |
Bibtex | baier+dubslaff++2021_from |
Scopus | 85115288464 |
ORCID | /0000-0003-4829-0476/work/165453928 |
Keywords
ASJC Scopus subject areas
Keywords
- Model Checking, Causality, Responsibility, Counterfactuals, Shapley value