Automated population of causal models for improved software risk assessment

Authors:
Peter Hearty;Norman Fenton;Martin Neil;Patrick Cates
Affiliations:
University of London, London, England;University of London, London, England;University of London, London, England;Agena Limited, London, England
Venue:
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Year:
2005

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Abstract

Recent work in applying causal modeling (Bayesian networks) to software engineering has resulted in improved decision support systems for software project managers. Once the causal models are built there are commercial tools that can run them. However, data to populate the models is typically entered manually and this is an impediment to their more widespread use. Hence, here we present a prototype tool for automatically extracting a range of relevant software metrics from popular project management and CASE tools. This information is used to populate Bayesian networks with the aim of providing better real world predictions of the risks associated with software costs, timescales and reliability.