Walkinshaw, N. (2020) Improving automated GUI testing by learning to avoid infeasible tests. In: Proceedings of the 2020 IEEE International Conference On Artificial Intelligence Testing (AITest). 2020 IEEE International Conference On Artificial Intelligence Testing (AITest), 03-06 Aug 2020, Oxford, UK. IEEE , pp. 107-114. ISBN 9781728169859
Abstract
Most modern end-user software applications are controlled through a graphical user interface (GUI). When it comes to automated test selection, however, GUIs present two major challenges: (1) It is difficult to automatically identify feasible, non-trivial sequences of GUI interactions (test cases), and (2) each attempt at a test case execution can take a long time, eliminating the possibility of rapidly attempting large numbers of alternatives. In this paper we present an iterative approach that infers state-machine models from previous test executions, and increases the utility of tests by learning which sequences to avoid. The approach is evaluated on a selection of Java applications, and the results indicate that our approach is successful at achieving higher code coverage and longer sequences than the state of the art, albeit with a time-overhead caused by the repeated invocation of a Machine Learner.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Graphical user interfaces; Testing; Tools; Inference algorithms; Androids; Humanoid robots; Automata |
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: | 17 Feb 2020 09:15 |
Last Modified: | 25 Aug 2021 00:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/AITEST49225.2020.00023 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157156 |