InProceedings{   renault.18.vecos,
  author        = {Etienne Renault},
  title         = {Improving Parallel State-Space Exploration Using Genetic
                  Algorithms},
  booktitle     = {Proceedings of the 12th International Conference on
                  Verification and Evaluation of Computer and Communication
                  Systems (VECOS'18)},
  editor        = {??},
  address       = {Grenoble, France},
  year          = 2018,
  month         = sept,
  pages         = {??--??},
  publisher     = {Springer},
  series        = {Lecture Notes in Computer Science},
  volume        = ??,
  abstract      = { The verification of temporal properties against a given
                  system may require the exploration of its full state
                  space. In explicit model-checking this exploration uses a
                  Depth-First-Search (DFS) and can be achieved with multiple
                  randomized threads to increase performance. Nonetheless
                  the topology of the state-space and the exploration order
                  can cap the speedup up to a certain number of
                  threads. This paper proposes a new technique that aims to
                  tackle this limitation by generating artificial initial
                  states, using genetic algorithms. Threads are then
                  launched from these states and thus explore different
                  parts of the state space. Our prototype implementation
                  runs 10\% faster than state-of-the-art algorithms. These
                  results demonstrate that this novel approach worth to be
                  considered as a way to overcome existing limitations.},
}