In software development, project constraints lead to customer-specific variants by copying and adapting the product. During this process, modifications are scattered all over the code. Although this is flexible and efficient in the short term, a Software Product Line (SPL) offers better results in the long term, regarding cost reduction, time-to-market, and quality attributes. This book presents a novel approach named SPLevo, which consolidates customized product copies into an SPL.

This handbook distils the wealth of expertise and knowledge from a large community of researchers and industrial practitioners in Software Product Lines (SPLs) gained through extensive and rigorous theoretical, empirical, and applied research. It is a timely compilation of well-established and cutting-edge approaches that can be leveraged by those facing the prevailing and daunting challenge of re-engineering their systems into SPLs. The selection of chapters provides readers with a wide and diverse perspective that reflects the complementary and varied expertise of the chapter authors. This perspective covers the re-engineering processes, from planning to execution. SPLs are families of systems that share common assets, allowing a disciplined software reuse. The adoption of SPL practices has shown to enable significant technical and economic benefits for the companies that employ them. However, successful SPLs rarely start from scratch, but instead, they usually start from a set of existing systems that must undergo well-defined re-engineering processes to unleash new levels of productivity and competitiveness. Practitioners will benefit from the lessons learned by the community, captured in the array of methodological and technological alternatives presented in the chapters of the handbook, and will gain the confidence for undertaking their own re-engineering challenges. Researchers and educators will find a valuable single-entry point to quickly become familiar with the state-of-the-art on the topic and the open research opportunities; including undergraduate, graduate students, and R&D engineers who want to have a comprehensive understanding of techniques in reverse engineering and re-engineering of variability-rich software systems.

This book constitutes the refereed proceedings of the 23rd Brazilian Symposium on Formal Methods, SBMF 2020, which was supposed to take place in Ouro Preto, Brazil, in November 2020. Instead the symposium took place virtually due to the COVID-19 pandemic. The 10 regular papers presented together with 3 invited talks in this book were carefully reviewed and selected from 17 submissions. The papers are organized in topical sections such as: experience reports; models, languages and semantics; and software product lines. Chapter ‘Safety Assurance of a High Voltage Controller for an Industrial Robotic System’ is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

The two-volume set LNCS 9952 and LNCS 9953 constitutes the refereed proceedings of the 7th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2016, held in Imperial, Corfu, Greece, in October 2016. The papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. Featuring a track introduction to each section, the papers are organized in topical sections named: statistical model checking; evaluation and reproducibility of program analysis and verification; ModSyn-PP: modular synthesis of programs and processes; semantic heterogeneity in the formal development of complex systems; static and runtime verification: competitors or friends?; rigorous engineering of collective adaptive systems; correctness-by-construction and post-hoc verification: friends or foes?; privacy and security issues in information systems; towards a unified view of modeling and programming; formal methods and safety certification: challenges in the railways domain; RVE: runtime verification and enforcement, the (industrial) application perspective; variability modeling for scalable software evolution; detecting and understanding software doping; learning systems: machine-learning in software products and learning-based analysis of software systems; testing the internet of things; doctoral symposium; industrial track; RERS challenge; and STRESS.