Abstract. While there are many excellent acceptance testing tools and frameworks available today, this paper presents an alternative approach, involving generating code from tests ...
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
Abstract. This paper presents our pattern-based approach to run-time requirements monitoring and threat detection being developed as part of an approach to build frameworks support...
This paper outlines an ontology for characterising architecture frameworks. The ontology is based on the metamodel of MAF, and is currently being tried out on a set of well-known e...
We present new results from a real-user evaluation of a data-driven approach to learning user-adaptive referring expression generation (REG) policies for spoken dialogue systems. ...