Improved decision-making for software managers using Bayesian networks

  • Authors:

  • Łukasz Radliński;Norman Fenton;Martin Neil;David Marquez

  • Affiliations:

  • University of Szczecin and University of London, London, UK;University of London, London, UK;University of London, London, UK;University of London, London, UK

  • Venue:
  • SEA '07 Proceedings of the 11th IASTED International Conference on Software Engineering and Applications
  • Year:
  • 2007

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Abstract

Although there have been many models for predicting quality and resources in software development, they do not provide enough decision-support for software managers. It has been argued that models based on Bayesian Nets (BNs) address this problem. Unlike previous BN models, the new model (called the Productivity Model) presented here takes account of both up-to-date generic empirical data on software productivity and quality and, where relevant, local information and choice of units of measurement. The model provides comprehensive support for 'trade-off' analysis to help decision-making.