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With software playing an increasingly important role in medical devices, regulatory agencies such as the US Food and Drug Administration need effective means for assuring that this software is safe and reliable. The FDA has been striving for a more rigorous engineering-based review strategy to provide this assurance. The use of mathematics-based techniques in the development of software might help accomplish this. However, the lack of standard architectures for medical device software and integrated engineering-tool support for software analysis make a science-based software review process more difficult. The research presented here applies formal modeling methods and static analysis techniques to improve the review process. Regulation of medical device software encompasses reviews of device designs (premarket review) and device performance (postmarket surveillance). The FDA's Center for Devices and Radiological Health performs the premarket review on a device to evaluate its safety and effectiveness. As part of this process, the agency reviews software development life-cycle artifacts for appropriate quality-assurance attributes, which tend to reveal little about the device software integrity.