License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.07161.9
URN: urn:nbn:de:0030-drops-13875
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1387/
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Baskiotis, Nicolas ;
Sebag, Michele
Structural Sampling for Statistical Software Testing
Abstract
Structural Statistical Software Testing exploits the control flow
graph of the program being tested to construct test cases.
While test cases can easily be extracted from {em feasible paths} in the control
flow graph, that is, paths which are actually exerted for some
values of the program input, the feasible path region is a tiny fraction
of the graph paths (less than $10^{-5}]$ for medium size programs).
The S4T algorithm presented in this paper aims to address this limitation;
as an Active Relational Learning Algorithm, it uses the few feasible paths
initially available to sample new feasible paths. The difficulty comes
from the non-Markovian nature of the feasible path concept, due to the
long-range dependencies between the nodes in the control flow graph.
Experimental validation on real-world and artificial problems
demonstrates significant improvements compared to the state of the art.
BibTeX - Entry
@InProceedings{baskiotis_et_al:DagSemProc.07161.9,
author = {Baskiotis, Nicolas and Sebag, Michele},
title = {{Structural Sampling for Statistical Software Testing}},
booktitle = {Probabilistic, Logical and Relational Learning - A Further Synthesis},
pages = {1--13},
series = {Dagstuhl Seminar Proceedings (DagSemProc)},
ISSN = {1862-4405},
year = {2008},
volume = {7161},
editor = {Luc de Raedt and Thomas Dietterich and Lise Getoor and Kristian Kersting and Stephen H. Muggleton},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2008/1387},
URN = {urn:nbn:de:0030-drops-13875},
doi = {10.4230/DagSemProc.07161.9},
annote = {Keywords: Active Relational Learning, Software Testing, Autonomic Computing, Parikh Maps}
}
Keywords: |
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Active Relational Learning, Software Testing, Autonomic Computing, Parikh Maps |
Collection: |
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07161 - Probabilistic, Logical and Relational Learning - A Further Synthesis |
Issue Date: |
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2008 |
Date of publication: |
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06.03.2008 |