The feasibility of inferring functional dependencies from an example relation is investigated. The problem occurs in the context of automatic database design, when a tool is needed to assist the database designer in the process of specifying logical dependencies. The complexity of the dependency inference problem is inherently exponential. However, algorithms could be developed that perform well when the input relation has certain characteristics. Two such algorithms for dependency inference are implemented and optimized. An extensive set of experiments is presented, in which dependencies were inferred from example relations with different cardinalities, number of attributes, and degree of normalization. It is concluded that for practical example relations, an adequate implementation of a dependence inference function leads to acceptable interactive response times.>