@InBook{LopezHerrejon2016,
  author    = {Roberto E. Lopez-Herrejon and Javier Ferrer and Francisco Chicano and Alexander Egyed and Enrique Alba},
  editor    = {Pedrycz, Witold and Succi, Giancarlo and Sillitti, Alberto},
  pages     = {59--87},
  publisher = {Springer International Publishing},
  title     = {Evolutionary Computation for Software Product Line Testing: An Overview and Open Challenges},
  year      = {2016},
  address   = {Cham},
  isbn      = {978-3-319-25964-2},
  abstract  = {Because of economical, technological and marketing reasons today's software systems are more frequently being built as families where each product variant implements a different combination of features. Software families are commonly called Software Product Lines (SPLs) and over the past three decades have been the subject of extensive research and application. Among the benefits of SPLs are: increased software reuse, faster and easier product customization, and reduced time to market. However, testing SPLs is specially challenging as the number of product variants is usually large making it infeasible to test every single variant. In recent years there has been an increasing interest in applying evolutionary computation techniques for SPL testing. In this chapter, we provide a concise overview of the state of the art and practice in SPL testing with evolutionary techniques as well as to highlight open questions and areas for future research.},
  booktitle = {Computational Intelligence and Quantitative Software Engineering},
  doi       = {10.1007/978-3-319-25964-2_4},
  url       = {https://doi.org/10.1007/978-3-319-25964-2_4},
}