A theoretical runtime and empirical analysis of different alternating variable searches for search-based testing

Authors:
Joseph Kempka;Phil McMinn;Dirk Sudholt
Affiliations:
University of Sheffield, Sheffield, United Kingdom;University of Sheffield, Sheffield, United Kingdom;University of Sheffield, Sheffield, United Kingdom
Venue:
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Year:
2013

Citing 13
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Abstract

The Alternating Variable Method (AVM) has been shown to be a surprisingly effective and efficient means of generating branch-covering inputs for procedural programs. However, there has been little work that has sought to analyse the technique and further improve its performance. This paper proposes two new local searches that may be used in conjunction with the AVM, Geometric and Lattice Search. A theoretical runtime analysis shows that under certain conditions, the use of these searches is proven to outperform the original AVM. These theoretical results are confirmed by an empirical study with four programs, which shows that increases of speed of over 50% are possible in practice.