Automatic test case generation is a key ingredient of an efficient and cost-effective software verification process. In this paper we focus on testing applications that interact with the users through a GUI, and present AutoBlackTest, a technique to automatically generate test cases at the system level. AutoBlackTest uses reinforcement learning, in particular Q-Learning, to learn how to interact with the application under test and stimulate its functionalities. The empirical results show that AutoBlackTest can execute a relevant portion of the code of the application under test, and can reveal previously unknown problems by working at the system level and interacting only through the GUI.
Mariani, L., Pezze', M., Riganelli, O., Santoro, M. (2012). AutoBlackTest: Automatic Black-Box Testing of Interactive Applications. In Proceedings of the Fifth International Conference on Software Testing Verification and Validation (ICST) (pp.81-90) [10.1109/ICST.2012.88].
AutoBlackTest: Automatic Black-Box Testing of Interactive Applications
MARIANI, LEONARDO;PEZZE', MAURO;RIGANELLI, OLIVIERO;SANTORO, MAURO
2012
Abstract
Automatic test case generation is a key ingredient of an efficient and cost-effective software verification process. In this paper we focus on testing applications that interact with the users through a GUI, and present AutoBlackTest, a technique to automatically generate test cases at the system level. AutoBlackTest uses reinforcement learning, in particular Q-Learning, to learn how to interact with the application under test and stimulate its functionalities. The empirical results show that AutoBlackTest can execute a relevant portion of the code of the application under test, and can reveal previously unknown problems by working at the system level and interacting only through the GUI.
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