Obsolescence, aging, reliability, and performance issues are driving nuclear facilities to replace conventional analog Instrumentation and Control (I&C) systems with digital technologies. In addition, the designs of the next generation of nuclear reactors, including Small Modular Reactors (SMRs), will incorporate digital I&C for most, if not all, of their safety and non-safety related functions. As part of a research and development (R&D) effort under the auspices of the U.S. Department of Energy (DOE), Analysis and Measurement Services Corporation (AMS) developed a platform to provide automated testing of digital I&C systems and create a standard method of evaluation for reliability assessments. This hands-on R&D effort has produced a Software Reliability Tester (SRT), which is a set of software tools designed to automate the testing of digital I&C systems to measure and quantify how well the system performs under normal operating conditions and in the presence of faults. Furthermore, the SRT provides the foundation for a practical tool to automate verification and validation (V&V) activities and reduce the amount of testing time of digital I&C systems. When combined with its capabilities of integrating both reliability and fault tolerance quantification, the SRT can be used to ensure that digital I&C implementations are both safe and cost-effective for the nuclear industry. This paper describes the application of the SRT with fault injection to automate V&V activities for a new Digital Rod Position Indication (DRPI) coil diagnostic system. The DRPI coil diagnostic system is a digital system that monitors the DRPI coil voltages of typical DRPI systems in nuclear power plants to detect and diagnose faults. For this application, the SRT was configured to exercise the inputs of the DRPI coil diagnostic system during rod movement while exposing the system to electromagnetic interference (EMI) at various amplitudes and frequencies. These test cases were applied by the SRT hardware as voltage inputs to the DRPI coil diagnostic system and the outputs were compared to expected values generated by a model of the DRPI coil diagnostic system. Included in the paper is a description of the overall design of the SRT including the hardware and software architectures. As described in the paper, V&V using the SRT demonstrates the benefits of automated testing and fault tolerance qualification to provide a quantitative assessment of reliability and cost effective implementation of digital I&C in existing and next generation nuclear power plants.