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Automatic testing of GUI‐based applications
Author(s) -
Mariani Leonardo,
Pezzè Mauro,
Riganelli Oliviero,
Santoro Mauro
Publication year - 2014
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/stvr.1538
Subject(s) - computer science , graphical user interface , graphical user interface testing , complement (music) , interface (matter) , user interface , human–computer interaction , cover (algebra) , software engineering , programming language , operating system , user interface design , engineering , mechanical engineering , biochemistry , chemistry , bubble , maximum bubble pressure method , complementation , gene , phenotype
SUMMARY Testing GUI‐based applications is hard and time consuming because it requires exploring a potentially huge execution space by interacting with the graphical interface of the applications. Manual testing can cover only a small subset of the functionality provided by applications with complex interfaces, and thus, automatic techniques are necessary to extensively validate GUI‐based systems. This paper presents 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. When used to complement the activity of test designers, AutoBlackTest reuses the information in the available test suites to increase its effectiveness. The empirical results show that AutoBlackTest can sample better than state of the art techniques the behaviour of the application under test and can reveal previously unknown problems by working at the system level and interacting only through the graphical user interface. Copyright © 2014 John Wiley & Sons, Ltd.