Automated population of causal models for improved software risk assessment

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. Categories and Subject Descriptors D.2.9 [Software Engineering]: Management – cost estimation, time estimation, software quality assurance. D.2.8 [Software Engineering]: Metrics – process metrics, product metrics. K.6.1 [Management of Computing and Information Systems]: Project and People ...

• Type: Conference
• Year: 2005
• Where: KBSE
• Authors: Peter Hearty, Norman E. Fenton, Martin Neil, Patrick Cates
• Keywords: Bayesian Networks, KBSE 2005, Software, Software Engineering