The problem of resource-constrained scheduling of testing tasks for new product development is addressed. The problem is important because, in some industries like pharmaceutical and agrochemicals, a new product is required to pass all the tests by federal laws. If a product fails any of the tests, then all the remaining work on that product is halted and the investment in the previous tests is wasted. Continuous time mixed-integer linear-programming models based on two different respresentations of resource constraints are presented to solve this scheduling problem. These models take into account complex trade-offs and have the capability of deriving a schedule that satisfies the resource constraints and utilizes the option of outsourcing. It is demonstrated with the second model, which is based on graph representation and makes use of logic, that the proper combination of modeling and search strategy can make the difference in successfully tackling this problem. Finally, it is also shown that it is critical to incorporate resource constraints along with sequencing of testing tasks to obtain a globally optimal solution.