Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Gaining Confidence in Software Inspection Using a Bayesian Belief Model
Software Quality Control
Sequential Model Criticism in Probabilistic Expert Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Modelling for Software Quality Control
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A conservative theory for long term reliability growth prediction
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
Safety critical software process improvement by multi-objective optimization algorithms
ICSP'07 Proceedings of the 2007 international conference on Software process
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Software safety standards recommend techniques to use throughout the software development lifecycle. These recommendations are a result of consensus building amongst software safety experts. Thus the reasoning underpinning compliance to these standards tends to be quite subjective. In addition, there are factors such as the size of the project, the effect of a review process on earlier phases of the development lifecycle, the complexity of the design and the quality of the staff, that arguably influence the assessment process but are not formally addressed by software safety standards. In this paper we present an expert system based on Bayesian Belief networks that take into account these and other factors when assessing the integrity at which the software was developed. This system has been reviewed by engineers working with software safety standard IEC61508. In this paper we illustrate some arguments that can be supported using the proposed system. This paper and the work it describes were partly funded by the Health and Safety Executive. The opinions or conclusions expressed are those of the authors alone and do not necessarily represent the views of the Health and Safety Executive.