As complexity increases, model-based approaches have become standard in the systems engineering community. However, engineers from different domains approach the system/component development at different levels of abstraction. Information gaps are created because of their different perspectives. In addition, although systems have become more complex, requiring more attention to testing, system methodologies have not kept up. A new framework is needed to bridge the information gaps between the different domains. To take full advantage of both model-based approaches and testing, we propose a new framework, in the form of a new design structure matrix, for complex system development (CSD) that more effectively utilizes information flow from model-based testing (MBT). Toward the goal of being broadly applicable, the framework was designed to be fundamental, flexible, and scalable. A case study of a powertrain design demonstrates how the proposed framework bridges gaps in early development stages. The analysis of both simulation and field testing results has shown that utilization of feedback from MBT refines requirements by closing information gaps earlier. All the information loops in the framework match the information loops in the case study. Furthermore, the framework, because of CSD's iterative nature, has potential in improving information reuse.