Recent years have seen the emergence of droplet-based microfluidic systems for safety-critical biomedical applications. In order to ensure reliability, microsystems incorporating microfluidic components must be tested adequately. In this paper, we investigate test planning and test resource optimization methods for droplet-based microfluidic arrays. We first outline a methodology based on integer linear programming (ILP) that yields optimal solutions. Due to the NP-complete nature of the problem, we develop heuristic approaches for optimization. Experimental results indicate that for large array sizes, heuristic methods yield solutions that are close to provable lower bounds. These heuristics ensure scalability and low computation cost.