This Small Business Technology Transfer (STTR) Phase I research project is to investigate the "good enough to release" decision for computer-based systems, and develop a decision support tool prototype based on the results of the investigation. This release decision, hereinafter referred to as the GETR decision, is fraught with uncertainty, since it is not possible to have complete knowledge of a system's true state before release. There is, then, always an element of risk when making the decision. The research in this project is aimed at mitigating this risk through understanding and support. Research objectives include validating a proposed GETR decision model of qualitative and quantitative evidence shown to be effective indicators of system quality, validating an innovative method for populating the model using expert opinion, and developing and validating sensitivity and uncertainty analyses. One of the broader impacts of the research is that gaining a better understanding of GETR decision elements and dynamics benefits more in society than the target audience for the decision support tool. Incorporating the findings from this project into release decisions would result in more informed release decisions, which would benefit both system owners and end users. Another of the broader impacts of the research is the transferability of the knowledge gained to similar decisions. The research can stand as a model for similar explorations of assessments of characteristics of computer-based systems, supporting research into areas such as evaluation of system dependability characteristics such as reliability, safety, security, availability, maintainability, and integrity. The project also provides a means for enhancing research partnerships, affording chances for learning. Prior work on the research topic has led to the strengthening of current research partnerships and the development of additional partnerships among government research centers and universities. Also, research partnerships have developed through the process of eliciting expert opinion used as input for model population and processing.
