Searching for invariants using genetic programming and mutation testing

Ratcliff, S., White, D.R. and Clark, J.A. (2011) Searching for invariants using genetic programming and mutation testing. In: Lanzi, P.L. (ed.) GECCO '11': Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation. Association for Computing Machinery: New York, NY, USA, pp. 1907-1914. ISBN 9781450305570 (doi: 10.1145/2001576.2001832)

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Abstract

Invariants are concise and useful descriptions of a program's behaviour. As most programs are not annotated with invariants, previous research has attempted to automatically generate them from source code. In this paper, we propose a new approach to invariant generation using search. We reuse the trace generation front-end of existing tool Daikon and integrate it with genetic programming and a mutation testing tool. We demonstrate that our system can find the same invariants through search that Daikon produces via template instantiation, and we also find useful invariants that Daikon does not. We then present a method of ranking invariants such that we can identify those that are most interesting, through a novel application of program mutation.

Item Type:Book Sections
Additional Information:© ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The original paper was presented at GECCO 2011 in Dublin, Ireland; 12th - 16th July 2011.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:White, Dr David
Authors: Ratcliff, S., White, D.R., and Clark, J.A.
College/School:College of Science and Engineering > School of Computing Science
Publisher:Association for Computing Machinery
ISBN:9781450305570
Copyright Holders:Copyright © 2011 Association for Computing Machinery
First Published:First published in Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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