Learning to select software components
Valerie Maxville, Jocelyn Armarego, Chiou Peng Lam · Murdoch Research Repository (Murdoch University) · 2004
Developers using software components need to be confident in their selection of the most suitable component. Manual searching is time consuming and unlikely to be able to consider large numbers of components. The Context-driven Component Evaluation (CdCE) project is investigating ways to use Artificial Intelligence to assist the selection process. This paper describes our Machine Learning approach where we train a system to recognise candidates that match an ideal component specification. We utilise automated test generation techniques to create data for training the system. This results in a generic assessment system that can automatically short-list components for further investigation.