Robotic-supported Data Loss Detection in Android Applications

Abstract:Smartphones have become integral to modern life due to their diverse applications. However, the development of applications for these devices faces significant challenges, primarily due to two factors: (i) the diverse hardware and operating system versions that require testing across multiple configurations; and (ii) the imperative activity of testing the smartphone in a non-invasive way (similar to an end-user interaction), which is expensive, tedious and error-prone as it is usually carried out manually. In this context, robotic automation has emerged as an effective solution for addressing the diversity of smartphone systems and versions, and in performing some testing tasks non-invasively. In addition, automated robots facilitate quick, accurate, and repetitive testing, thus enabling developers to validate their applications across various configurations effectively. This results in a less invasive verification and in a significant reduction in time spent on manual testing, thus accelerating the development cycle. Our work proposes R-DLD (Robotic-supported Data Loss Detection), a robot-assisted infrastructure for data loss detection in Android applications, offeringless invasive and more realistic tests by interacting directly with smartphone sensors. The robot is constructed using cost-effective materials, facilitating its adoption in testing environments. In our empirical evaluation R-DLD successfully identified 341 data loss issues in 77 randomly selected apps from an Android store. All reported bugs received responses from the developer, with 89.55% confirming the data loss problems, while 35.82% have being subsequently fixed.

Software Engineering (cs.SE); Robotics (cs.RO)

arXiv:2610.20807 [cs.SE]

(or arXiv:2610.20807v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2610.20807 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

https://doi.org/10.5753/sbes.2024.2899 Focus to learn more DOI(s) linking to related resources

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