An extended systematic literature review on provision of evidence for safety certification <s> Quantitative Assessment (10%): <s> In this paper we describe an approach to capture the degree of compliance of a product with an industry standard such as the international standard for functional safety of E/E/PE systems, IEC 61508. We call this the evidential volume of an assessment scenario. It is based on compiling observed evidence according to assigned weighting factors, which describe the relative importance of each piece of evidence. The evidential volume can by itself be used as an indicator to compare different assessment scenarios. This could form the basis for improved consistency in assessment. We suggest a model to relate the evidential volume to the probability of having achieved a product of required safety integrity. Developing such a relationship can lead to a decision-aid on acceptance or rejection or can be used to decide whether additional evidence, such as statistical testing could be used to achieve target safety integrity. The model we suggest is based on the Success Likelihood Index Model (SLIM) and it poses an initial step towards decisionsupport for assessment. The model developed can be used for any standard, IEC 61508 is used as an example only. <s> BIB001 </s> An extended systematic literature review on provision of evidence for safety certification <s> Quantitative Assessment (10%): <s> 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. <s> BIB002
We classify in this category techniques that use numerical measures for assessment of evidence. These techniques are: , which assess evidence in the presence of uncertainty by using conditional probability distributions. This technique is used in conjunction with BBN structuring of evidence (Section 4.2). This is the most frequent quantitative technique in the literature for evidence assessment. The Modus approach BIB002 , which combines quantitative assessment with formal argumentation structures. The approach is based on quantitative reasoning that uses goal models (KAOS), expert elicitation, and probabilistic simulation for assessing the overall goal of a safety case. Evidence Volume Approach BIB001 , which allows an internal expert to assign weighted factors on evidence that describe the relative importance of each piece of evidence. An aggregate function is then chosen for the weighted evidence to calculate a volume known as evidence volume, based on which an outcome (accept or reject) is chosen.