@inproceedings{181,
  keywords = {Software Maintenance},
  author = {Farshad Toosi and Asanka Wasala and Goetz Botterweck and Jim Buckley},
  editor = {Hernán Aguirre and Keiki Takadama},
  title = {Identification of potential classes in procedural code using a genetic algorithm},
  abstract = {We present a novel approach for discovering and suggesting classes/objects in legacy/procedural code, based on a genetic algorithm. Initially, a (procedures-accessing-variables) matrix is extracted from the code and converted into a square matrix. This matrix highlights the variable-relationships between procedures and is used as input to a genetic algorithm. The output of the genetic algorithm is then visually encoded using a heat-map. The developers can then (1) either manually identify objects in the presented heat-map or (2) use an automated detection algorithm that suggests objects. We compare our results with previous work.},
  year = {2018},
  booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2018, Kyoto, Japan, July 15-19, 2018},
  journal = {Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2018, Kyoto, Japan, July 15-19, 2018},
  pages = {314-315},
  publisher = {ACM},
  url = {http://doi.acm.org/10.1145/3205651.3205720},
  doi = {10.1145/3205651.3205720},
  key = {bibcite_181},
}