Title
Combining Goal Models, Expert Elicitation, and Probabilistic Simulation for Qualification of New Technology
Abstract
New technologies typically involve innovative aspects that are not addressed by the existing normative standards and hence are not assessable through common certification procedures. To ensure that new technologies can be implemented in a safe and reliable manner, a specific kind of assessment is performed, which in many industries, e.g., the energy sector, is known as Technology Qualification (TQ). TQ aims at demonstrating with an acceptable level of confidence that a new technology will function within specified limits. Expert opinion plays an important role in TQ, both to identify the safety and reliability evidence that needs to be developed, and to interpret the evidence provided. Hence, it is crucial to apply a systematic process for eliciting expert opinions, and to use the opinions for measuring the satisfaction of a technology's safety and reliability objectives. In this paper, drawing on the concept of assurance cases, we propose a goal-based approach for TQ. The approach, which is supported by a software tool, enables analysts to quantitatively reason about the satisfaction of a technology's overall goals and further to identify the aspects that must be improved to increase goal satisfaction. The three main components enabling quantitative assessment are goal models, expert elicitation, and probabilistic simulation. We report on an industrial pilot study where we apply our approach for assessing a new offshore technology.
Year
DOI
Venue
2011
10.1109/HASE.2011.22
High-Assurance Systems Engineering
Keywords
Field
DocType
new technology,eliciting expert opinion,expert elicitation,goal satisfaction,goal-based approach,new offshore technology,probabilistic simulation,expert opinion,goal model,combining goal models,quantitative assessment,overall goal,uncertainty,goal modeling,monte carlo simulation,probabilistic logic,reliability,monte carlo methods
Systematic process,Expert elicitation,Computer science,Normative,Emerging technologies,Goal modeling,Probabilistic logic,Certification,Reliability engineering,Probabilistic simulation
Conference
ISSN
ISBN
Citations 
1530-2059
978-1-4673-0107-7
15
PageRank 
References 
Authors
0.84
5
7
Name
Order
Citations
PageRank
Mehrdad Sabetzadeh198861.84
Davide Falessi250434.89
Lionel C. Briand38795481.98
Stefano Di Alesio4877.57
Dag McGeorge5150.84
Vidar Åhjem6150.84
Jonas Borg7150.84