Home → Magazine Archive → November 2022 (Vol. 65, No. 11) → Research for Practice: Convergence → Abstract

Research for Practice: Convergence

By Martin Kleppmann, Peter Alvaro

Communications of the ACM, Vol. 65 No. 11, Pages 104-106
10.1145/3563901

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It is with great pride and no small amount of excitement that I announce the reboot of Research for Practice. Beginning at its inception in 2016, Research for Practice brought both seminal and cutting-edge research—via careful curation by experts in academia—within easy reach for practitioners who are too busy building things to manage the deluge of scholarly publications. We believe the series succeeded in its stated goal of sharing "the joy and utility of reading computer science research" between academics and their counterparts in industry. We are delighted to rekindle the flame after a three-year hiatus.

For this first installment, we invited Martin Kleppmann, research fellow and affiliated lecturer at the University of Cambridge, to curate a selection of recent research papers in a perennially interesting domain: convergent or "eventual consistent" replicated systems. His expert analysis circles the topic, viewing it through the lens of recent work in four distinct research domains: systems, programming languages, human-computer interaction, and data management. Along the way, readers will be exposed to a variety of data structures, algorithms, proof techniques, and programming models (each described in terms of a distinct formalism), all of which attempt to make programming large-scale distributed systems easier. I hope you enjoy his column as much as I did.
Peter Alvaro

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