Title
Automated Software Testing Based on Hierarchical State Transition Matrix for Smart TV.
Abstract
Smart TV in China as an important component of the smart home, does not only have the functions of the traditional TV, but also have the functions, such as distance education, remote monitoring, E-business, and media playing, which brings about its software to be more complex in structure and larger in scale, accordingly, the total testing efficiency becomes lower when using traditional testing methods, and the deep-hidden software defects cannot be detected efficiently and effectively. A novel automatic software testing method based on system design specifications is proposed to improve the smart TV software testing efficiency. First, the behavior of the smart TV is modeled, based on the system design specification with hierarchical state transition matrixes (HSTMs). The scale of the state model of the smart TV is lowered by setting the group state according to the choice of the key nodes based on the importance of the nodes in the network; then, the HSTM model is converted into an expanded regular expression (ERE) with the memory property. Second, every closure operator in the ERE is replaced recursively with a certain integral value, according to the cyclomatic complexity of an ERE in the closure to generate a simplified ERE. Then, a test case is generated from the simplified ERE. Finally, the test cases are converted into python script, and a test platform is designed to send the python script to the Android smart TV automatically through its android debug bridge interface. The practical application shows that the test period is shortened, and comparing with the traditional manual test methods, more errors can be tested.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2694880
IEEE ACCESS
Keywords
Field
DocType
Hierarchical state transition matrix,Cyclomatic complexity,expanded regular expressions,group state
Android (operating system),Computer science,Cyclomatic complexity,Systems design,Home automation,Software,Test case,Python (programming language),Embedded system,Debugging
Journal
Volume
ISSN
Citations 
5
2169-3536
1
PageRank 
References 
Authors
0.36
15
4
Name
Order
Citations
PageRank
Kai Cui161.18
Kuanjiu Zhou2188.56
Houbing Song31771172.26
Mingchu Li446978.10