Many automatic Web testing techniques generate test cases by analyzing the GUI of the Web applications under test, aiming to exercise sequences of actions that are similar to the ones that testers could manually execute. However, the efficiency of the test generation process is severely limited by the cost of analyzing the content of the GUI screens after executing each action. In this paper, we introduce an inference component, S, which accumulates knowledge about the behavior of the GUI after each action. S enables the test generators to reuse the results computed for GUI screens that recur multiple times during the test generation process, thus improving the efficiency of Web testing techniques. We experimented S with Web testing techniques based on three different GUI exploration strategies (Random, Depth-first, and Q-learning) and nine target systems, observing reductions from 22% to 96% of the test generation time

Clerissi, D., Denaro, G., Mobilio, M., Mariani, L. (2024). Guess the State: Exploiting Determinism to Improve GUI Exploration Efficiency. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 50(4), 836-853 [10.1109/TSE.2024.3366586].

Guess the State: Exploiting Determinism to Improve GUI Exploration Efficiency

Clerissi D.;Denaro G.;Mobilio M.;Mariani L.
2024

Abstract

Many automatic Web testing techniques generate test cases by analyzing the GUI of the Web applications under test, aiming to exercise sequences of actions that are similar to the ones that testers could manually execute. However, the efficiency of the test generation process is severely limited by the cost of analyzing the content of the GUI screens after executing each action. In this paper, we introduce an inference component, S, which accumulates knowledge about the behavior of the GUI after each action. S enables the test generators to reuse the results computed for GUI screens that recur multiple times during the test generation process, thus improving the efficiency of Web testing techniques. We experimented S with Web testing techniques based on three different GUI exploration strategies (Random, Depth-first, and Q-learning) and nine target systems, observing reductions from 22% to 96% of the test generation time
Articolo in rivista - Articolo scientifico
Behavioral sciences; Generators; Graphical user interfaces; Knowledge based systems; Q-learning; State inference; System testing; Test pattern generators; Testing; Web testing;
English
16-feb-2024
2024
50
4
836
853
none
Clerissi, D., Denaro, G., Mobilio, M., Mariani, L. (2024). Guess the State: Exploiting Determinism to Improve GUI Exploration Efficiency. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 50(4), 836-853 [10.1109/TSE.2024.3366586].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/462218
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