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Intermediate Value Linearizability: A Quantitative Correctness Criterion
2020
International Symposium on Distributed Computing
Big data processing systems often employ batched updates and data sketches to estimate certain properties of large data. For example, a CountMin sketch approximates the frequencies at which elements occur in a data stream, and a batched counter counts events in batches. This paper focuses on correctness criteria for concurrent implementations of such objects. Specifically, we consider quantitative objects, whose return values are from a totally ordered domain, with a particular emphasis on
doi:10.4230/lipics.disc.2020.2
dblp:conf/wdag/RinbergK20
fatcat:nu3fhf25hjgopd3qd6nrajnuma