Abstract: A new method of testcase optimization for generating testcases is provided which is both efficient and effective. A 2-level heuristic is employed. The method is iterative, and at each iteration, at the first level of the heuristic, a greedy algorithm is used to select a testcase which covers the largest number of uncovered interactions from a remaining set of uncovered interactions. The second level heuristic consists of a simulation step which is employed at each iteration. Rather than conducting the greedy algorithm over an entire test domain, during each iteration the algorithm is applied over a randomly selected set of testcases. The method is efficient in the sense that a quasi-optimal number of testcases is generated which covers the most interactions with close to the fewest number of testcases. The method is effective in the sense that 100% coverage of all possible interactions is guaranteed.