Genetic Configuration Sampling: Learning a Sampling Strategy for Fault Detection of Configurable Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

@InProceedings{Xuan:2018:GI5,
  author =       "Jifeng Xuan and Yongfeng Gu and Zhilei Ren and 
                 Xiangyang Jia and Qingna Fan",
  title =        "Genetic Configuration Sampling: Learning a Sampling
                 Strategy for Fault Detection of Configurable Systems",
  booktitle =    "5th edition of GI @ GECCO 2018",
  year =         "2018",
  editor =       "Brad Alexander and Saemundur O. Haraldsson and 
                 Markus Wagner and John R. Woodward and Shin Yoo",
  pages =        "wksp153s2",
  address =      "Kyoto, Japan",
  month =        "15-19 " # jul,
  organisation = "ACM SIGEvo",
  publisher =    "ACM",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, SBSE, Configuration sampling, fault
                 detection, highly-configurable systems, software
                 configurations",
  URL =          "http://www.cs.stir.ac.uk/events/gecco-gi-2018/papers/genetic_configuration_sampling.pdf",
  DOI =          "doi:10.1145/3205651.3208267",
  size =         "8 pages",
  abstract =     "A highly-configurable system provides many
                 configuration options to diversify application
                 scenarios. The combination of these configuration
                 options results in a large search space of
                 configurations. This makes the detection of
                 configuration-related faults extremely hard. Since it
                 is infeasible to exhaust every configuration, several
                 methods are proposed to sample a subset of all
                 configurations to detect hidden faults. Configuration
                 sampling can be viewed as a process of repeating a
                 pre-defined sampling action to the whole search space,
                 such as the one-enabled or pair-wise strategy.

                 we propose genetic configuration sampling, a new method
                 of learning a sampling strategy for
                 configuration-related faults. Genetic configuration
                 sampling encodes a sequence of sampling actions as a
                 chromosome in the genetic algorithm. Given a set of
                 known configuration-related faults, genetic
                 configuration sampling evolves the sequence of sampling
                 actions and applies the learnt sequence to new
                 configuration data. A pilot study on three
                 highly-configurable systems shows that genetic
                 configuration sampling performs well among nine
                 sampling strategies in comparison.",
  notes =        "Apache, BusyBox, Linux

                 'compiler Gcc 7.3 contains 2472 configuration
                 options'

                 http://www.cs.stir.ac.uk/events/gecco-gi-2018/cfp.html",
}

Genetic Programming entries for Jifeng Xuan Yongfeng Gu Zhilei Ren Xiangyang Jia Qingna Fan

Citations