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Robust derivation of risk reduction strategies

Show simple item record Richardson, Julian Port, Daniel Feather, Martin 2011-09-29T21:57:07Z 2011-09-29T21:57:07Z 2007-03-03
dc.identifier.citation IEEE Aerospace Conference, Big Sky, Montana, March 3-10, 2007. en_US
dc.identifier.clearanceno 07-0027
dc.description.abstract Effective risk reduction strategies can be derived mechanically given sufficient characterization of the risks present in the system and the effectiveness of available risk reduction techniques. In this paper, we address an important question: can we reliably expect mechanically derived risk reduction strategies to be better than fixed or hand-selected risk reduction strategies, given that the quantitative assessment of risks and risk reduction techniques upon which mechanical derivation is based is difficult and likely to be inaccurate? We consider this question relative to two methods for deriving effective risk reduction strategies: the strategic method defined by Kazman, Port et al [Port et al, 2005], and the Defect Detection and Prevention (DDP) tool [Feather & Cornford, 2003]. We performed a number of sensitivity experiments to evaluate how inaccurate knowledge of risk and risk reduction techniques affect the performance of the strategies computed by the Strategic Method compared to a variety of alternative strategies. The experimental results indicate that strategies computed by the Strategic Method were significantly more effective than the alternative risk reduction strategies, even when knowledge of risk and risk reduction techniques was very inaccurate. The robustness of the Strategic Method suggests that its use should be considered in a wide range of projects. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2007. en_US
dc.subject risk reduction en_US
dc.title Robust derivation of risk reduction strategies en_US
dc.type Preprint en_US

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