This paper deals with testing of nondeterministic software systems. We assume that a model of the nondeterministic system is given by a directed graph with two kinds of vertices: states and choice points. Choice points represent the nondeterministic behavior of the implementation under test (IUT). Edges represent transitions. They have costs and probabilities. Test case generation in this setting amounts to generation of a game strategy. The two players are the testing tool (TT) and the IUT. The game explores the graph. The TT leads the IUT by selecting an edge at the state vertices. At the choice points the control goes to the IUT. A game strategy decides which edge should be taken by the TT in each state. This paper presents three novel algorithms 1) to determine an optimal strategy for the bounded reachability game, where optimality means maximizing the probability to reach any of the given final states from a given start state while at the same time minimizing the costs of traversal; 2) to determine a winning strategy for the bounded reachability game, which guarantees that given final vertices are reached, regardless how the IUT reacts; 3) to determine a fast converging edge covering strategy, which guarantees that the probability to cover all edges quickly converges to 1 if TT follows the strategy.