Kempka, J., McMinn, P. and Sudholt, D. (2015) Design and analysis of different alternating variable searches for search-based software testing. Theoretical Computer Science, 605. pp. 1-20. ISSN 0304-3975
Abstract
Manual software testing is a notoriously expensive part of the software development process, and its automation is of high concern. One aspect of the testing process is the automatic generation of test inputs. This paper studies the Alternating Variable Method (AVM) approach to search-based test input generation. The AVM has been shown to be an 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 different local searches that may be used in conjunction with the AVM, Geometric and Lattice Search. A theoretical runtime analysis proves that under certain conditions, the use of these searches results in better performance compared to the original AVM. These theoretical results are confirmed by an empirical study with five programs, which shows that increases of speed of over 50% are possible in practice.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Search-based software engineering; Test data generation; Local search; Runtime analysis; Theory |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Jan 2016 16:16 |
Last Modified: | 20 Jan 2016 16:16 |
Published Version: | http://dx.doi.org/10.1016/j.tcs.2014.12.009 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.tcs.2014.12.009 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:93029 |