Today's column deals with the theory of computability in a distributed system. It features a tutorial on this topic by Maurice Herlihy, Sergio Rajsbaum, and Michel Raynal. The tutorial focuses on a canonical asynchronous computation model, where processes communicate by writing to and reading from shared memory. It studies which distributed tasks can be solved in this model in the presence of process failures and communication delays, and which cannot. The tutorial highlights two powerful

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... ques for obtaining computability results: First, the abstraction of an iterated write-snapshot model is used in order to simplify algorithms, and reduce the complexity of the solutions space one needs to explore for impossibility proofs. Second, concepts from combinatorial topology provide an understanding of the mathematical structure induced by possible executions of a protocol in this model. Many thanks to Maurice, Sergio, and Michel for their contribution! Call for contributions: I welcome suggestions for material to include in this column, including news, reviews, open problems, tutorials and surveys, either exposing the community to new and interesting topics, or providing new insight on well-studied topics by organizing them in new ways. Abstract What can and cannot be computed in a distributed system is a complex function of the system's communication model, timing model, and failure model. This tutorial surveys some important results about computability in the canonical distributed system model, where processes execute asynchronously, they communicate by reading and writing shared memory, and they fail by crashing. It explains the fundamental role that topology plays in the distributed computability theory.