A neural net based approach to Test Oracle-Reference-Cited by-同舟云学术

A neural net based approach to Test Oracle

Published:2004-05 Issue:3 Volume:29 Page:1-6
ISSN:0163-5948
Container-title:ACM SIGSOFT Software Engineering Notes
language:en
Short-container-title:SIGSOFT Softw. Eng. Notes

Author:

Aggarwal K. K.¹,Singh Yogesh¹,Kaur A.¹,Sangwan O. P.²

Affiliation:

1. G. G. S. Indraprastha University, Delhi, India

2. G. J. University, Hisar, Haryana, India

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.

Publisher

Association for Computing Machinery (ACM)

Link

https://dl.acm.org/doi/pdf/10.1145/986710.986725

Reference19 articles.

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. API-Knowledge Aware Search-Based Software Testing: Where, What, and How;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

2. Software Testing Combining the Fusion of Surrogate Model and Evolutionary Algorithm;2023 International Conference on the Cognitive Computing and Complex Data (ICCD);2023-10-21

3. CirFix: Automated Hardware Repair and its Real-World Applications;IEEE Transactions on Software Engineering;2023-07

4. The integration of machine learning into automated test generation: A systematic mapping study;Software Testing, Verification and Reliability;2023-05-02

5. Machine learning‐based test oracles for performance testing of cyber‐physical systems: An industrial case study on elevators dispatching algorithms;Journal of Software: Evolution and Process;2022-05-25