The use of scenarios has become a popular technique for requirements elicitation and specification building. Since scenarios capture only partial descriptions of system behavior, ...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
The development of object-oriented software starts from requirements expressed commonly as Use Cases. The requirements are then converted into a conceptual or analysis model. Analy...
First-order probabilistic models are recognized as efficient frameworks to represent several realworld problems: they combine the expressive power of first-order logic, which serv...
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...