Machine learning components are essential for today's software systems, causing a need to
adapt traditional software engineering practices when developing machine-learning-based …

Handling large-scale software variability is still a challenge for many organizations. After
decades of research on variability management concepts, many industrial organizations …

Software reuse lowers development costs and improves the quality of software systems. Two
strategies are common: clone & own (copying and adapting a system) and platform-oriented …

Safety and security are important properties of any software system, particularly in safety-
critical domains, such as embedded, automotive, or cyber-physical systems. Moreover …

Process models for software product-line engineering focus on proactive adoption scenarios-
--that is, building product-line platforms from scratch. They comprise the two phases domain …

Abstract Version control systems are an integral part of today's software engineering. They
facilitate the collaborative management of revisions (sequential versions) and variants …

Robots artificially replicate human capabilities thanks to their software, the main
embodiment of intelligence. However, engineering robotics software has become …

Many techniques were proposed for detecting software misconfigurations in cloud systems
and for diagnosing unintended behavior caused by such misconfigurations. Detection and …

Customization is a general trend in software engineering, demanding systems that support
variable stakeholder requirements. Two opposing strategies are commonly used to create …

Machine Learning (ML) techniques are becoming essential components of many software
systems today, causing an increasing need to adapt traditional software engineering …