article

A neural net based approach to Test Oracle

Authors:

K. K. Aggarwal,

O. P. SangwanAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 29, Issue 3

Pages 1 - 6

https://doi.org/10.1145/986710.986725

Published: 01 May 2004 Publication History

Abstract

In this paper an attempt has been made to explore the possibility of the usage of artificial neural networks as Test Oracle. The triangle classification problem has been used as a case study. Results for the usage of unsupervised artificial networks indicate that they are not suitable for this purpose. The Feed-forward back propagation neural networks are demonstrated to be suitable.

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cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 29, Issue 3

May 2004

102 pages

ISSN:0163-5948

DOI:10.1145/986710

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Copyright © 2004 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 May 2004

Published in SIGSOFT Volume 29, Issue 3

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Cited By

Wang XAli SArrieta AArcaini PArratibel Md'Amorim M(2024)Application of Quantum Extreme Learning Machines for QoS Prediction of Elevators’ Software in an Industrial ContextCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663859(399-410)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3663529.3663859
Ren XYe XLin YXing ZLi SLyu MChandra SBlincoe KTonella P(2023)API-Knowledge Aware Search-Based Software Testing: Where, What, and HowProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3616269(1320-1332)Online publication date: 30-Nov-2023
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https://dl.acm.org/doi/10.1109/TSE.2023.3269899
Dang XBao WQu QLi D(2023)Software Testing Combining the Fusion of Surrogate Model and Evolutionary Algorithm2023 International Conference on the Cognitive Computing and Complex Data (ICCD)10.1109/ICCD59681.2023.10420549(311-316)Online publication date: 21-Oct-2023
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Fontes AGay G(2023)The integration of machine learning into automated test generation: A systematic mapping studySoftware Testing, Verification and Reliability10.1002/stvr.184533:4Online publication date: 2-May-2023
https://doi.org/10.1002/stvr.1845
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Taromirad MRuneson P(2022)Near Failure Analysis Using Dynamic Behavioural DataProduct-Focused Software Process Improvement10.1007/978-3-031-21388-5_12(171-178)Online publication date: 21-Nov-2022
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