<pre>Variability has become a prominent facet of virtually every modern software–intensive system we engineer and use today. Variability can manifest itself in many different forms, ranging from platform support to configure a system aligned with the needs of a particular user or usage up to the ability of a system to autonomously reconfigure itself to maintain its quality goals while facing uncertain operating conditions. To effectively exploit and manage variability, it is crucial that it is treated as a first–class citizen throughout the life time of a system. Since its inception, the variability management community has devised many breakthroughs in the foundations that underly variability as well as its engineering principles and application to a broad variety domains and contexts. The ever changing landscape of software–intensive systems raises new challenges to variability researchers and engineers. For example, machine learning techniques revolutionise decision making in various systems, in particular variability–intensive ones. The DeVops paradigm can exploit variability modelling and management when integrating features, code and tests in continuous integration and delivery cycles. The growing number of smart city applications that are currently rolled out necessarily need to rely on software that dynamically adapts itself when these systems face new situations. Variability can play a key role in managing this adaptivity in a trustworthy manner. VaMoS 2019 aims to establish bridges between variability modelling communities and other fields, such as DeVops, Artificial Intelligence (AI), Self–Adaptation, and Internet–of–Things. To initiate such bridges, VaMoS will feature one panel on Variability and AI and invite for two other panels one via an open call. The VaMoS series aims to bring together researchers from different areas dedicated to mastering variability by presenting innovative solutions that tackle the open challenges, discuss tradeoffs and complementarities of various approaches, and demonstrate how stakeholders of different application domains can benefit for novel variability solutions. Topics include but are not limited to: – Variability management throughout the life cycle – Variability modelling and realisation – Variability–driven runtime adaptation – Variability and context–aware approaches – Variability and quality requirements – Variability and security – Variability in continuous * (DevOps) – Testing, formal reasoning and automated analysis on variability models – Refactoring and evolution of variability intensive software systems – Variability and current technologies (micro–services, cloud, edge, etc.) – Variability and AI (machine learning, meta–heuristics, etc.) – Variability in autonomous systems (autonomous cars, drones, etc.) – Variability and blockchain technology – Variability in the Internet–of–Things – Variability and configuration management – Variability mining and reverse engineering approaches – Visualisation techniques for variability models and systems – Software economic aspects of variability</pre>
Abbrevation
VaMoS
City
Leuven
Country
Belgium
Deadline Paper
Start Date
End Date
Abstract