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Peixin You

dblp:390/3228 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0002-8035-5209ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 67% Storage systems · 33%
Software engineering, system software, and programming languages
1 paper
Concurrent programming · 50% Program verification · 50%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Concurrent programming › atomicity
linearizability
0.812024
Compositionality and Observational Refinement for Linearizability with Crashes · Proc. ACM Program. Lang. 2024
Program verification
program logic
0.812024
Compositionality and Observational Refinement for Linearizability with Crashes · Proc. ACM Program. Lang. 2024
Storage systems
crash safety
0.812024
Compositionality and Observational Refinement for Linearizability with Crashes · Proc. ACM Program. Lang. 2024
Distributed systems › consistency models
durable linearizability
0.812024
Compositionality and Observational Refinement for Linearizability with Crashes · Proc. ACM Program. Lang. 2024
Distributed systems
fault tolerance
0.812024
Compositionality and Observational Refinement for Linearizability with Crashes · Proc. ACM Program. Lang. 2024

Methods — techniques the papers use, named apart from their topics

program logic · 1.5observational refinement · 1.5compositional semantics · 1.5
YearPublicationVenuePosition
2024 Compositionality and Observational Refinement for Linearizability with Crashes
abstract
Crash-safety is an important property of real systems, as the main functionality of some systems is resilience to crashes. Toward a compositional verification approach for crash-safety under full-system crashes, one observes that crashes propagate instantaneously to all components across all levels of abstraction, even to unspecified components, hindering compositionality. Furthermore, in the presence of concurrency, a correctness criterion that addresses both crashes and concurrency proves necessary. For this, several adaptations of linearizability have been suggested, each featuring different trade-offs between complexity and expressiveness. The recently proposed compositional linearizability framework shows that to achieve compositionality with linearizability, both a locality and observational refinement property are necessary. Despite that, no linearizability criterion with crashes has been proven to support an observational refinement property. In this paper, we define a compositional model of concurrent computation with full-system crashes. We use this model to develop a compositional theory of linearizability with crashes, which reveals a criterion, crash-aware linearizability , as its inherent notion of linearizability and supports both locality and observational refinement. We then show that strict linearizability and durable linearizability factor through crash-aware linearizability as two different ways of translating between concurrent computation with and without crashes, enabling simple proofs of locality and observational refinement for a generalization of these two criteria. Then, we show how the theory can be connected with a program logic for durable and crash-aware linearizability, which gives the first program logic that verifies a form of linearizability with crashes. We showcase the advantages of compositionality by verifying a library facilitating programming persistent data structures and a fragment of a transactional interface for a file system.
Arthur Oliveira Vale, Zhongye Wang, Yixuan Chen 0002, Peixin You, Zhong Shao 0001
Proc. ACM Program. Lang.4