In safety-critical systems, the verification and validation phase in the software development life cycle plays an important role in assuring safety. The artifacts' outputs of the verification and validation processes represent the evidence needed to show a satisfactory fulfillment of the safety requirements. Providing strong evidence to show that the requirements of the domain standards are met is the core of demonstrating safety standards compliance. In this paper, we propose a systematic approach for verifying safety-critical systems efficiently by integrating model-based testing, combinatorial testing, and safety analysis; this is all driven by providing safety assurance. The approach provides both testing and formal verification capabilities, and it is easy to implement into a tool for use in an industry setting. To show how our approach could contribute to safety standards compliance, we investigated it's capability to fulfill the safety requirements by analyzing and linking the data produced from the steps in the approach to a safety evidence taxonomy.