Please use this identifier to cite or link to this item: https://elib.vku.udn.vn/handle/123456789/3192
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dc.contributor.authorNguyen, Thanh Binh-
dc.contributor.authorLe, Thi Thanh Binh-
dc.contributor.authorAktouf, Oum-El-Kheir-
dc.contributor.authorParissis, Ioannis-
dc.date.accessioned2023-10-05T09:16:18Z-
dc.date.available2023-10-05T09:16:18Z-
dc.date.issued2022-08-
dc.identifier.isbn978-3-031-15063-0 (e)-
dc.identifier.urihttps://doi.org/10.1007/978-3-031-15063-0_20-
dc.identifier.urihttp://elib.vku.udn.vn/handle/123456789/3192-
dc.descriptionInternational Conference on Intelligence of Things (ICIT 2022); Lecture Notes on Data Engineering and Communications Technologies, Vol.148; pp: 215-225.vi_VN
dc.description.abstractNowadays, mobile smartphones are being widely used. They allow users to access a variety of services provided by mobile applications (mobile apps). These services are location-based services, meaning that a user’s location is taken into consideration for service provision. Testing these mobile apps is challenging due to the complexity of context variability (i.e., a user’s location). Current testing approaches cannot efficiently handle dynamic variability of mobile apps. To solve this problem, this paper introduces a model-based testing approach of mobile apps that uses a combination of a Bigraphical Reaction System (BRS) model and a Dynamic feature Petri net (DFPN) for automatic generation of test cases. Our model addresses the mobile app testing challenges related to the context of mobile apps, and especially to changes in the context location.vi_VN
dc.language.isoenvi_VN
dc.publisherSpringer Naturevi_VN
dc.subjectMobile applications testingvi_VN
dc.subjectBigraphsvi_VN
dc.subjectDynamic feature Petri netsvi_VN
dc.titleMobile Applications Testing Based on Bigraphs and Dynamic Feature Petri Netsvi_VN
dc.typeWorking Papervi_VN
Appears in Collections:NĂM 2022

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