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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5320))

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Abstract

The Defect Detection and Prevention (DDP) decision support process, developed at JPL, has over the last 8 years been applied to assist in making a variety of spacecraft decisions. It was originally conceived of as a means to help select and plan hardware assurance activities (inspections, tests, etc) [1], generally late in the development lifecycle. However, since then it has been used predominantly in early phase of system design, when information is scarce, yet many critical decisions are made. Its range of application has extended to encompass a wide variety of kinds of systems and technologies. Its predominant role has been to assist in planning the maturation of promising new technologies to help guide the next steps in their development as they emerge from the laboratory and seek to mature sufficiently to become acceptable to spacecraft missions [2]. Although this may at first glance seem far removed from terrestrial considerations, the factors that come into play in this kind of decision-making are universal - unclear and inconsistent perceptions about requirements and capabilities, uncertainty of what are the driving concerns that should be addressed and how best to address them, challenges of gathering and combining information from experts of multiple difference disciplines, and inevitably the lack of sufficient resources (money, time, CPU, power, ...) to do everything one would wish. Other significant applications of DDP have been as the risk management tool for entire spacecraft projects in their early phases of development, as an aid to planning portfolios of mission activities (e.g., [3]), and as a means to help guide R&D decisions (e.g., [4], [5]).

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References

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© 2008 Springer-Verlag Berlin Heidelberg

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Feather, M.S. (2008). Defect Detection and Prevention (DDP). In: Paech, B., Martell, C. (eds) Innovations for Requirement Analysis. From Stakeholders’ Needs to Formal Designs. Monterey Workshop 2007. Lecture Notes in Computer Science, vol 5320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89778-1_4

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  • DOI: https://doi.org/10.1007/978-3-540-89778-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89777-4

  • Online ISBN: 978-3-540-89778-1

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