Data and Analysis Code for GP EFSM Inference

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Hall:2016:ICSME,
  author =       "Mathew Hall and Neil Walkinshaw",
  booktitle =    "2016 IEEE International Conference on Software
                 Maintenance and Evolution (ICSME)",
  title =        "Data and Analysis Code for GP EFSM Inference",
  year =         "2016",
  pages =        "611--611",
  abstract =     "This artefact captures the workflow that we adopted
                 for our experimental evaluation in our ICSME paper on
                 inferring state transition functions during EFSM
                 inference. To summarise, the paper uses Genetic
                 Programming to infer data transformations, to enable
                 the inference of fully 'computational' extended finite
                 state machine models. This submission shows how we
                 generated, transformed, analysed, and visualised our
                 raw data. It includes everything needed to generate raw
                 results and provides the relevant R code in the form of
                 a re-usable Jupyter Notebook (accompanied by a
                 descriptive narrative).",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICSME.2016.22",
  month =        oct,
  notes =        "Also known as \cite{7816520}",
}

Genetic Programming entries for Mathew Hall Neil Walkinshaw

Citations