Recommender systems are decision support systems that help users to identify items of
relevance from a potentially large set of alternatives. In contrast to the mainstream …

Constraint solving is applied in different application contexts. Examples thereof are the
configuration of complex products and services, the determination of production schedules …

The number of new vulnerabilities continues to rise significantly each year. Simultaneously,
vulnerability databases have challenges in promptly sharing new security events with …

Feature models are the de facto standard for modelling variabilities and commonalities in
features and relationships in software product lines. They are the base artefacts in many …

Constraint-based applications attempt to identify a solution that meets all defined user
requirements. If the requirements are inconsistent with the underlying constraint set …

Challenging domains of the future such as Smart Cities, Cloud Computing, or Industry 4.0
expose highly variable systems with colossal configuration spaces. The automated analysis …

Diagnosis, ie, the detection and identification of faults, provides the basis for bringing
systems back to normal operation in case of a fault. Diagnosis is a very important task of our …

Sports recommender systems receive an increasing attention due to their potential of
fostering healthy living, improving personal well-being, and increasing performances in …

This open access book provides a basic introduction to feature modelling and analysis as
well as to the integration of AI methods with feature modelling. It is intended as an …

Variability models (eg, feature models) are a common way for the representation of
variabilities and commonalities of software artifacts. Such models can be translated to a …