Data and Analysis Code for GP EFSM Inference
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Hall:2016:ICSME,
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author = "Mathew Hall and Neil Walkinshaw",
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booktitle = "2016 IEEE International Conference on Software
Maintenance and Evolution (ICSME)",
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title = "Data and Analysis Code for GP EFSM Inference",
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year = "2016",
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pages = "611--611",
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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).",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICSME.2016.22",
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month = oct,
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notes = "Also known as \cite{7816520}",
- }
Genetic Programming entries for
Mathew Hall
Neil Walkinshaw
Citations