In the context of the Multiparty Interaction Model, fairness is used to insure that an interaction that isenabled sufficiently often in a concurrent program will eventually be selected for execution. Unfortunately,this notion does not take conspiracies into account, i.e. situations in which an interaction never becomesenabled because of an unfortunate interleaving of independent actions; furthermore, eventual execution isusually too weak for practical purposes since this concept can only be used in the context of infiniteexecutions. In this article, we present a new fairness notion, k-conspiracy-free fairness, that improves onothers because it takes finite executions into account, alleviates conspiracies that are not inherent to aprogram, and k may be set a priori to control its goodness to address the above-mentioned problems.
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