TY - GEN
T1 - A New Approach to Assessment of Confidence in Assurance Cases
AU - Zhao, Xingyu
AU - Zhang, Dajian
AU - Lu, Minyan
AU - Zeng, Fuping
PY - 2012
Y1 - 2012
N2 - An assurance case is a body of evidence organized into an argument demonstrating that some claims about a system hold. It is generally developed to support claims in areas such as safety, reliability, maintainability, human factors, security etc. Practically, both argument and evidence are imperfect, resulting in that we can hardly say the claim is one hundred percent true. So when we do decision-making against assurance cases, we need to know how much confidence we hold in the claims. And the quantitative confidence would provide benefits over the qualitative one. In this paper, an approach is proposed to assess the confidence in assurance cases (mainly arguments) quantitatively. First we convert Argument Metamodel based (ARM-based) cases into a set of Toulmin model instances; then we use Hitchcock's evaluative criteria for solo-verb-reasoning to analyze and quantify the Toulmin model instances into Bayesian Belief Network (BBN); running the Bayesian Belief Network, we get quantified confidence from each claim of the assurance case. Finally, we illustrate our approach by using a simplified fragment from safety cases and discuss several future work.
AB - An assurance case is a body of evidence organized into an argument demonstrating that some claims about a system hold. It is generally developed to support claims in areas such as safety, reliability, maintainability, human factors, security etc. Practically, both argument and evidence are imperfect, resulting in that we can hardly say the claim is one hundred percent true. So when we do decision-making against assurance cases, we need to know how much confidence we hold in the claims. And the quantitative confidence would provide benefits over the qualitative one. In this paper, an approach is proposed to assess the confidence in assurance cases (mainly arguments) quantitatively. First we convert Argument Metamodel based (ARM-based) cases into a set of Toulmin model instances; then we use Hitchcock's evaluative criteria for solo-verb-reasoning to analyze and quantify the Toulmin model instances into Bayesian Belief Network (BBN); running the Bayesian Belief Network, we get quantified confidence from each claim of the assurance case. Finally, we illustrate our approach by using a simplified fragment from safety cases and discuss several future work.
KW - Assurance case
KW - Bayesian Belief Network
KW - informal logic
KW - quantified confidence
KW - Toulmin model
UR - http://www.scopus.com/inward/record.url?scp=84868113642&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33675-1_7
DO - 10.1007/978-3-642-33675-1_7
M3 - Conference contribution
AN - SCOPUS:84868113642
SN - 9783642336744
T3 - Lecture Notes in Computer Science
SP - 79
EP - 91
BT - Computer Safety, Reliability, and Security
A2 - Ortmeier, Frank
A2 - Daniel, Peter
PB - Springer
T2 - 31st International Conference on Computer Safety, Reliability and Security 2012
Y2 - 25 September 2012 through 28 September 2012
ER -