Testing model transformations requires input models which are graphs of inter-connected objects that must conform to a meta-model and meta-constraints from heterogeneous sources su...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
higher, more appropriate, level of abstraction. It still entails writing programs, usually by using symbols, keywords, and operational instructions to tell the computer what we wan...
Synchronous programming languages have proved to be advantageous for designing software and hardware for embedded systems. Despite their clear semantics, their compilation is rema...
: We present new valid inequalities for 0-1 programming problems that work in similar ways to well known cover inequalities. Discussion and analysis of these cuts is followed by th...