Abstract. We investigate the use of parameterized state machine models to drive integration testing, in the case where the models of components are not available beforehand. Theref...
Planning techniques recorded a significant progress during recent years. However, many planning problems remain still hard even for modern planners. One of the most promising appro...
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
This paper demonstrates two methods to improve the performance of instancebased learning (IBL) algorithms for the problem of Semantic Role Labeling (SRL). Two IBL algorithms are u...
Abstract. By combining algorithmic learning, decision procedures, predicate abstraction, and simple templates, we present an automated technique for finding quantified loop invaria...