J. Kontio and V. Basili. Empirical evaluation of a risk management method. In Proceedings of the SEI Conference on Risk Management, Pittsburgh, PA, 1997. Home/Search Document Details and Download
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The Riskit Method for Software Risk Management, version 1.00 - Kontio Self-citation (Kontio) (Correct)
....report, readers interested in that aspect of the method are kindly asked to refer to other publications [29 31] or contact the author for more information or for more recent publications. An earlier version of the Riskit method has been empirically evaluated in a limited number of case studies [19,30,31]. This current version of the method (version 1.00) has been improved based on the feedback received from several case studies or evaluations carried out in industry and government organizations. This paper is organized as follows. Chapter 3 presents key terminology in one place, although all ....
....and utility loss associated with each scenario. These two estimation problems have different kinds of inherent difficulties. Probability estimation is difficult because little historical data may be available and event probabilities, in principle, are unknowable in a changing environment [23,30]. Utility loss estimation is difficult because there are multiple factors to be considered and the exact shapes and forms of stakeholders utility functions are not known. We will discuss the estimation problems for each aspect of risk separately in the following. If historical data about risks ....
J. Kontio and V.R. Basili, Empirical Evaluation of a Risk Management Method 1997. Proceedings of the SEI Conference on Risk Management. Software Engineering Institute. Pittsburgh, PA.
Experiences in improving risk management processes using.. - Kontio, Getto, al. (1998) Self-citation (Kontio) (Correct)
....5 scenario 6 . Risk scenario Utility loss rank m scenario 7 Table 2: Risk scenario ranking table using Pareto efficient sets elicit utility loss preferences from stakeholders. 4 Empirical Study Goals and Design We have conducted several case studies for evaluating the Riskit method [11,21,22]. In this paper we present the findings from our empirical studies at Daimler Benz AG and Nokia Telecommunications corporation. In the following we will present the case study design, organizations and their earlier risk management practices, as well as the findings from the case studies. 4.1 ....
.... Threats Case studies are prone to many limitations, compared to situations where large amounts of data can be collected and analyzed [25,27] Studies in risk management, in particular, have even more serious constraints that limit the choice of experimental designs and available data points [21], as well as challenges in construct validity. In particular, low number of data points, their non random selection, and variance in situational characteristics limit the external validity of the results obtained, i.e. their generalizability. Our case studies tried to limit the internal validity ....
J. Kontio and V.R. Basili, Empirical Evaluation of a Risk Management Method 1997. Proceedings of the SEI Conference on Risk Management. Software Engineering Institute. Pittsburgh, PA.
Risk Knowledge Capture in the Riskit Method - Kontio, Basili (1996) (1 citation) Self-citation (Kontio Basili) (Correct)
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J. Kontio and V. R. Basili, Empirical Evaluation of a Risk Management Method, 1997. Proceedings of the SEI Conference on Risk Management. Software Engineering Institute. Pittsburgh, PA.
Knowledge-based Risk Assessment for Intelligent Vehicles - Lattner, Timm, Lorenz, Herzog (2005) (Correct)
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J. Kontio and V. Basili. Empirical evaluation of a risk management method. In Proceedings of the SEI Conference on Risk Management, Pittsburgh, PA, 1997.
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