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https://dx.doi.org/10.48550/ar...
Article . 2021
License: CC BY
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On the Monitorability of Session Types, in Theory and Practice (Extended Version)

Authors: Christian Bartolo Burlò; Adrian Francalanza; Alceste Scalas;

On the Monitorability of Session Types, in Theory and Practice (Extended Version)

Abstract

In concurrent and distributed systems, software components are expected to communicate according to predetermined protocols and APIs - and if a component does not observe them, the system's reliability is compromised. Furthermore, isolating and fixing protocol/API errors can be very difficult. Many methods have been proposed to check the correctness of communicating systems, ranging from compile-time to run-time verification; among such methods, session types have been applied for both static type-checking, and run-time monitoring. This work takes a fresh look at the run-time verification of communicating systems using session types, in theory and in practice. On the theoretical side, we develop a novel formal model of session-monitored processes; with it, we formulate and prove new results on the monitorability of session types, connecting their run-time and static verification - in terms of soundness (i.e., whether monitors only flag ill-typed processes) and completeness (i.e., whether all ill-typed processes can be flagged by a monitor). On the practical side, we show that our monitoring theory is indeed realisable: building upon our formal model, we develop a Scala toolkit for the automatic generation of session monitors. Our executable monitors can be used to instrument black-box processes written in any programming language; we assess the viability of our approach with a series of benchmarks.

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Keywords

FOS: Computer and information sciences, Computer Science - Programming Languages, Programming Languages (cs.PL)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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