Strongly Normalizing Audited Computation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Auditing is an increasingly important operation for computer programming, for example in security (e.g. to enable history-based access control) and to enable reproducibility and accountability (e.g. provenance in scientific programming). Most proposed auditing techniques are ad hoc or treat auditing as a second-class, extralinguistic operation; logical or semantic foundations for auditing are not yet well-established. Justification Logic (JL) offers one such foundation; Bavera and Bonelli introduced a computational interpretation of JL called $\lambda^h$ that supports auditing. However, $\lambda^h$ is technically complex and strong normalization was only established for special cases. In addition, we show that the equational theory of $\lambda^h$ is inconsistent. We introduce a new calculus $\lambda^{hc}$ that is simpler than $\lambda^h$, consistent, and strongly normalizing. Our proof of strong normalization is formalized in Nominal Isabelle.
Original languageEnglish
Title of host publication26th EACSL Annual Conference on Computer Science Logic (CSL 2017)
PublisherSchloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany
Pages1-21
Number of pages21
ISBN (Print)978-3-95977-045-3
DOIs
Publication statusPublished - 24 Aug 2017
Event26th EACSL Annual Conference on Computer Science Logic - Stockholm, Sweden
Duration: 20 Aug 201724 Aug 2017
https://www.math-stockholm.se/konferenser-och-akti/logic-in-stockholm-2/26th-eacsl-annual-co/computer-science-logic-2017-august-20-24-1.717663

Publication series

NameLeibniz International Proceedings in Informatics (LIPIcs)
PublisherSchloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Volume82
ISSN (Print)1868-8969

Conference

Conference26th EACSL Annual Conference on Computer Science Logic
Abbreviated titleCSL 2017
Country/TerritorySweden
CityStockholm
Period20/08/1724/08/17
Internet address

Keywords / Materials (for Non-textual outputs)

  • cs.LO

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