Abstract Machine learning (ML) provides algorithms to create computer programs based on
data without explicitly programming them. In business process management (BPM), ML …

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

In the last years, cyber-physical systems (CPS) are receiving substantial mainstream
attention especially in industrial environments, but this popularity has been accompanied by …

Unsupervised feature selection (UFS) is utilized in various application domains, such as
data mining, pattern recognition, machine learning, etc. UFS follows three basic approaches …

Data centres have become the backbone of large Cloud services and applications,
providing virtually unlimited elastic and scalable computational and storage resources. The …

Variability models are used to build configurators, for guiding users through the
configuration process to reach the desired setting that fulfils user requirements. The same …

Cybersecurity attacks affect the compliance of cybersecurity policies of the organisations.
Such disadvantages may be due to the absence of security configurations or the use of …

Conflict detection is used in various scenarios ranging from interactive decision making (eg,
knowledge-based configuration) to the diagnosis of potentially faulty models (eg, using …

From business processes to course management, variability-intensive software systems
(VIS) are now ubiquitous. One can configure these systems' behaviour by activating options …

Process mining as a modeling and analysis tool can be used to improve the business
performance by looking at the actual business processes. This paper presents the …