@Conference{DBLP:conf/icsm/LinsbauerAGLPLE14,
  author    = {Lukas Linsbauer and Florian Angerer and Paul Grünbacher and Daniela Lettner and Herbert Prähofer and Roberto E. Lopez{-}Herrejon and Alexander Egyed},
  title     = {Recovering Feature-to-Code Mappings in Mixed-Variability Software Systems},
  booktitle = {30th {IEEE} International Conference on Software Maintenance and Evolution, Victoria, BC, Canada, September 29 - October 3, 2014},
  year      = {2014},
  pages     = {426--430},
  abstract  = {Software engineering methods for analyzing and
managing variable software systems rely on accurate featureto-
code mappings to relate high-level variability abstractions,
such as features or decisions, to locations in the code where
variability occurs. Due to the continuous and long-term evolution
of many systems such mappings need to be extracted
and updated automatically. However, current approaches have
limitations regarding the analysis of highly-configurable systems
that rely on different variability mechanisms. We present a novel
approach that exploits the synergies between program analysis
and diffing techniques to reveal feature-to-code mappings for
highly-configurable systems. We demonstrate the feasibility of
our approach with a set of products from a real-world product
line in the domain of industrial automation.},
  bibsource = {dblp computer science bibliography, https://dblp.org},
  biburl    = {https://dblp.org/rec/bib/conf/icsm/LinsbauerAGLPLE14},
  crossref  = {DBLP:conf/icsm/2014},
  doi       = {10.1109/ICSME.2014.67},
  file      = {:Conferences\\ICSME 2014 - Recovering Feature-to-Code Mappings in Mixed-Variability Software Systems\\Recovering Feature-to-Code Mappings in Mixed-Variability Software Systems-preprint.pdf:PDF},
  timestamp = {Mon, 22 May 2017 17:11:02 +0200},
  url       = {https://doi.org/10.1109/ICSME.2014.67},
}