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2016 | OriginalPaper | Chapter

Neural Network-Based Automated Priority Assigner

Authors : Harsh Bhasin, Esha Khanna, Kapil Sharma

Published in: Proceedings of the Second International Conference on Computer and Communication Technologies

Publisher: Springer India

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Abstract

The testing of a system starts with the crafting of test cases. Not all the test cases are, however, equally important. The test cases can be prioritized using policies discussed in the work. The work proposes a neural network model to prioritize the test cases. The work has been validated using backpropagation neural network. 200 test cases were crafted and the experiment was carried out using 2, 5, 10, 15, and 20 layers neural network. The results have been reported and lead to the conclusion that neural network-based priority analyzer can predict the priority of a test.

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Literature
1.
Aggarwal, D., Tamir, D., Last, M., Kandel, A.: A comparative study of artificial neural network and info fuzzy network as automated oracles in software testing. IEEE Trans. Syst. Man Cybern. 42(5), (2012)
2.
Anderson, C., Mayrhauser, A., Marz, R.: On the use of neural networks to guide software testing activities. In: International Test Conference IEEE (1995)
3.
Beizer, B.: Software Testing Techniques (2nd Ed.). Van Nostrand Reinhold Co., New York, NY, USA (1990)
4.
Bertolino, A.: A Brief Essay on Software Testing, vol. 1. Wiley-IEEE (2005)
5.
Bhasin, H.: Artificial life and cellular automata based automated test case generator. ACM SIGSOFT Softw. Eng. Notes 39(1), 1–5 (2014)
6.
Bhasin, H.: Regression testing using genetic algorithms. (IJCSIT) Int. J. Comput. Sci. Inf. Technol. (2012)
7.
Bhasin, H., Khanna, E.: Neural network based black box testing. ACM SIGSOFT Softw. Eng. Notes 39(4), 1–6 (2014)
8.
Bhasin, H., Singla, N.: Cellaur-genetic test data generation. ACM SIGSOFT Softw. Eng. Notes 38(5), (2013)
9.
Bhasin, H., Gupta, S., Kathuria, M.: Implementation of regression testing using fuzzy logic. Int. J. Appl. Innovation Eng. Manage. (2003)
10.
Bhasin, H., Shewani, Goyal, D.: Test data generation using artificial life. Int. J. Comput. Appl. 67(12), (2013)
11.
Bhasin, H., Singla, N., Sharma, S.: Cellular automata based test data generation. ACM SIGSOFT Softw. Eng. Notes 38(4), 1–6 (2013)
12.
Jorgensen, P.C.: Software Testing A Craftman’s Approach. CRC Press (1995)
13.
Kaner, C., Falk, J., Nguyen, H.Q.: Testing Computer Software. Wiley (1999)
14.
Khan, E., Khan, F.: A comparative study of white box, black box and grey box testing techniques. Int. J. Adv. Comput. Sci. Appl. 3(6), (2012)
15.
Kitchenham, B., et al.: Systematic literature reviews in software engineering-A systematic literature review. Inf. Softw. Technol. 51(1), 7–15 (January 2009)
16.
Larry, V., Kirkland, R., Glenn, W.: Using Neural Network for Functional Testing. IEEE (1995)
17.
Myers, G.: The Art of Software Testing. Wiley (2004)
18.
Paul, A.L., Byrne, P.: An Efficient Learning Algorithm for the Back Propagation Artificial Neural Network. IEEE (1990)
19.
Saraph, P., Last, M., Kandel, A.: Test set generation and reduction with artificial neural networks. In: Last, D.M., Kandel, A., Bunke, H. (eds.) Artificial Intelligence Methods in Software Testing. World Scientific (2004)
20.
Vanamali, M., Last, M., Kandel, A.: Using neural network in the software testing process. Int. J. Intell. Syst. 17(1), (2002)
21.
Wu, L., Liu, B., Jin, Y., Xie, X.: Using back-propagation neural networks for functional software testing. In Anti-counterfeiting, Security and Identification,ASID 2008. 2nd International Conference (2008)
Metadata
Title
Neural Network-Based Automated Priority Assigner
Authors
Harsh Bhasin
Esha Khanna
Kapil Sharma
Copyright Year
2016
Publisher
Springer India
Book
Proceedings of the Second International Conference on Computer and Communication Technologies

Print ISBN: 978-81-322-2525-6

Electronic ISBN: 978-81-322-2526-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-81-322-2526-3_20