An axiomatic approach to reversible computation
File(s)
Published version
Author(s)
Lanese, Ivan
Phillips, Iain
Ulidowski, Irek
Type
Conference Paper
Abstract
Undoing computations of a concurrent system is beneficial inmany situations, e.g., in reversible debugging of multi-threaded programsand in recovery from errors due to optimistic execution in parallel dis-crete event simulation. A number of approaches have been proposed forhow to reverse formal models of concurrent computation including pro-cess calculi such as CCS, languages like Erlang, prime eventstructuresand occurrence nets. However it has not been settled what properties areversible system should enjoy, nor how the various properties that havebeen suggested, such as the parabolic lemma and the causal-consistencyproperty, are related. We contribute to a solution to these issues by usinga generic labelled transition system equipped with a relationcapturingwhether transitions are independent to explore the implications betweenthese properties. In particular, we show how they are derivable from aset of axioms. Our intention is that when establishing properties of someformalism it will be easier to verify the axioms rather than proving prop-erties such as the parabolic lemma directly. We also introduce two newnotions related to causal consistent reversibility, namely causal safetyand causal liveness, and show that they are derivable from our axioms.
Date Issued
2020-04-17
Date Acceptance
2019-12-21
Citation
2020, pp.442-461
Publisher
Springer
Start Page
442
End Page
461
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unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative
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you will need to obtain permission directly from the copyright holder.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are
believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors
give a warranty, expressed or implied, with respect to the material contained herein or for any errors or
omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International
License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution
and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and
the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this book are included in the book’s Creative Commons license,
unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative
Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use,
you will need to obtain permission directly from the copyright holder.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are
believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors
give a warranty, expressed or implied, with respect to the material contained herein or for any errors or
omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
License URL
Identifier
https://link.springer.com/chapter/10.1007%2F978-3-030-45231-5_23
Source
23rd International Conference on Foundations of Software Science and Computation Structures (FoSSaCS 2020)
Subjects
Artificial Intelligence & Image Processing
Publication Status
Published
Start Date
2020-04-25
Finish Date
2020-05-01
Coverage Spatial
Dublin, Ireland
Date Publish Online
2020-04-17