Enhancing Test Cases Prioritization for Internet of Things based systems using Search-based Technique
Mohamed, N., Moussa, S., Badr, N., Tolba, M. (2021). Enhancing Test Cases Prioritization for Internet of Things based systems using Search-based Technique. EKB Journal Management System, 21(1), 84-94. doi: 10.21608/ijicis.2021.69462.1076
Noha Medhat Mohamed; Sherin Moussa; Nagwa Badr; Mohamed Tolba. "Enhancing Test Cases Prioritization for Internet of Things based systems using Search-based Technique". EKB Journal Management System, 21, 1, 2021, 84-94. doi: 10.21608/ijicis.2021.69462.1076
Mohamed, N., Moussa, S., Badr, N., Tolba, M. (2021). 'Enhancing Test Cases Prioritization for Internet of Things based systems using Search-based Technique', EKB Journal Management System, 21(1), pp. 84-94. doi: 10.21608/ijicis.2021.69462.1076
Mohamed, N., Moussa, S., Badr, N., Tolba, M. Enhancing Test Cases Prioritization for Internet of Things based systems using Search-based Technique. EKB Journal Management System, 2021; 21(1): 84-94. doi: 10.21608/ijicis.2021.69462.1076

Enhancing Test Cases Prioritization for Internet of Things based systems using Search-based Technique

International Journal of Intelligent Computing and Information Sciences
Article 7, Volume 21, Issue 1, February 2021, Page 84-94  XML PDF (779.91 K)
Document Type: Original Article
DOI: 10.21608/ijicis.2021.69462.1076
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Authors
Noha Medhat Mohamed email orcid 1; Sherin Moussaorcid 2; Nagwa Badrorcid 1; Mohamed Tolbaorcid 3
1Department of Information Systems, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, 11566, Egypt
2Department of Information Systems, Faculty of Computer and Information Scences
3Department of Scientific Computing, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, 11566, Egypt
Abstract
Test cases prioritization has been excessively considered for continious regression and integration testing in Internet of Things based systems to apply multilevel testing activities. Various number of devices, sensors and acctuators are connected together through the internet using different technologies, which requires extensively testing the effeciency of these components and the transferred data between them. Due to the number of the connected components has dramatically increased, causing a direct proportional increase in the number of test cases.Studies that handle the augmentation of the number of test cases for traditional systems lack effeciency when applied for Internet of Things based systems. In this paper, we introduce an enhancement for test cases prioritization using Hill Climbing algorithm as a local search based technique, adapted to achieve tangible effeciency. It is integrated with the LSTM deep learning algorithm for test cases classification purposes. The results of the test cases prioritization using Hill Climbing for regression and integration testing are evaluated using precision, where it achieved 80% and 97% for regression testing, and 93% and 88% for integration testing using two Internet of Things-based system datasets.
Keywords
Deep learning; Integration testing; Internet of Things based systems; Regression testing; Test case prioritization
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