SEBASE: Software Engineering By Automated SEarch

The SEBASE project aimed to provide a new approach to the way in which software engineering is understood and practised. Its goal was to move software engineering problems from human-based search to machine-based search. As a result, human effort moves up the abstraction chain, to focus on guiding the automated search, rather than performing it. This project addressed key issues in software engineering, including scalability, robustness, reliability and stability. It also studied theoretical foundations of search algorithms and apply the insights gained to develop more effective and efficient search algorithms for large and complex software engineering problems. These insights from the project had a major impact on the search algorithm community as well as the software engineering community.


Status Finished
UoY Lead Iain Bate
UoY People on Project Simon Poulding, Paul Emberson, David White, Philippa Conmy, Chen Hao, Kamran Ghani, Peter Laurens, Jan Staunton
Partners University College London, University of York, University of Birmingham
Funded By EPSRC
Start Date 01-06-2006
End Date 31-12-2011
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