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Monte Carlo Modelling |
O X F O R D S O F T W A R E E N G I N
E E R I N G |
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Statistical
and probabilistic methods for more predictable software projects and processes…
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Recent developments in statistical modelling and new software tools are making innovative methods available to software organizations that want to increase project predictability, reduce risks and increase their understanding of software development activities. But new methods and tools alone are not enough. They have to be used accountably and well if they are not to mislead planners and undermine confidence in estimates and the evaluation of risks. Software development is complex and subtle (even if it doesn’t always appear that way). Every software development environment and every project is unique. A sound understanding of your environment and its projects is essential if statistical or probabilistic methods are to be developed correctly and used well. Only with this understanding can models and simulations be used in a robust and accountable manner. We have worked across many industry sectors, in software
organizations of all sizes and are a leader in helping software organizations
analyse, understand and increase the performance of their development and
test environments. And we have the background in the application of
measurement and statistical modelling techniques to software development. We are ideally placed to help you give your organization
an edge with the powerful new methods and tools you need to improve
estimation, increase project predictability and manage risks more
effectively. If you want to get the best from your Monte Carlo
simulations, Bayesian networks or other statistical modelling tools, to
better manage your software development and would like help with: -
software process modelling, -
methods or tool selection, -
selecting distribution types, -
statistical model development, -
running and analysing your simulations, or simply validate your existing models then contact us now to find out we can help you. CCS
November 2008 |
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© Copyright OSEL 2008 |
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