Probabilistic datatypes

Chris Chen, Annabelle McIver*, Carroll Morgan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

An encapsulated datatype collects related data together with the operations used to access them. Datatype refinement then provides a clear separation between the expectations of programs that call the operations (i.e. from outside the encapsulation) and the implementation of the operations themselves (inside the encapsulation), and it enforces consistency between the two. 

In this paper we consider encapsulated probabilistic datatypes, i.e. those whose operations can “flip coins”; and we find as a result that the interface between calling programs’ expectations and their encapsulated probabilistic implementations must now provide consistency not only for functional properties but also for properties related to information flow. 

In this paper we use a quantitative information-flow model for programs to give a sound basis for refinement of probabilistic datatypes.

Original languageEnglish
Title of host publicationTheoretical Aspects of Computing – ICTAC 2024
Subtitle of host publication21st International Colloquium, Bangkok, Thailand, November 25–29, 2024, proceedings
EditorsChutiporn Anutariya, Marcello M. Bonsangue
Place of PublicationCham
PublisherSpringer, Springer Nature
Pages3-16
Number of pages14
ISBN (Electronic)9783031770197
ISBN (Print)9783031770180
DOIs
Publication statusPublished - 2025
Event21st International Colloquium on Theoretical Aspects of Computing, ICTAC 2024 - Bangkok, Thailand
Duration: 25 Nov 202429 Nov 2024

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume15373
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Colloquium on Theoretical Aspects of Computing, ICTAC 2024
Country/TerritoryThailand
CityBangkok
Period25/11/2429/11/24

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