Petri nets are commonly used to represent concurrent systems. However, they lack support for modelling and analysing system families, like variants of controllers, different variations of a process model, or the possible configurations of a flexible assembly line. To facilitate modelling potentially large collections of similar systems, in this paper, we enrich Petri nets with variability mechanisms based on product line engineering. Moreover, we present methods for the efficient analysis of the place and transition invariants in all defined versions of a Petri net. Efficiency is achieved by analysing the system family as a whole, instead of analysing each possible net variant separately. For this purpose, we lift the notion of incidence matrix to the product line level, and rely on constraint solving techniques. We present tool support and evaluate the benefits of our techniques on synthetic and realistic examples, achieving in some cases speed-ups of two orders of magnitude with respect to analysing each net variant separately.

Petri nets are a popular formalism to model and analyse concurrent systems.They can be combined with software product lines to support the specification of concurrent system families, like variants of controllers, process models, or configurations of flexible assembly lines.Specifically, a Petri net product line (PNPL) comprises a (black and white) Petri net decorated with variability inscriptions, and a feature model controlling the derivation of admissible nets of the family.However, the derivable nets cannot be reconfigured at runtime, and the techniques to analyse properties of such reconfigurations are limited.To tackle these issues, we present a method to embed a PNPL into a standard Coloured Petri net.This embedding permits using the extensive simulation and analysis capabilities of powerful tools like CPN Tools, and enables the reconfiguration of the product nets at run-time.In this paper, we report on the translation of PNPLs into Coloured Petri nets, characterize the properties that can be analysed with this translation, and describe tool support on the basis of a case study in the area of flexible production systems.

The General Data Protection Regulation (GDPR) is the core of digital privacy legislation across Europe (EU), and it applies to processing carried out by organisations operating within and outside the EU that offer goods or services to individuals in the EU, including software products.Nevertheless, software teams are generally unaware of the legal requirements for personal data protection and its application throughout the software life cycle.In this paper, we propose a comprehensive guidance to integrate compliance with GDPR requirements within the Unified Software Development Process (UP) across the entire lifetime.

Model-based development approaches, such as Model-Driven Engineering (MDE), heavily rely on the use of modelling languages to achieve and automate software development tasks. To enable the definition of model variants (e.g., supporting the compact description of system families), one solution is to combine MDE with Software Product Lines. However, this is technically costly as it requires adapting many MDE artefacts associated to the modelling language -- especially the meta-models and graphical environments. To alleviate this situation, we propose a method for the automated injection of variability into graphical modelling languages. Given the meta-model and graphical environment of a particular language, our approach permits configuring the allowed model variability, and the graphical environment is automatically adapted to enable creating models with variability. Our solution is implemented atop the Eclipse Modeling Framework and Sirius, and synthesizes adapted graphical editors integrated with FeatureIDE.