References of "Cotroneo, Domenico"
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See detailDependability Assessment of the Android OS Through Fault Injection
Iannillo, Antonio Ken UL; Cotroneo, Domenico; Natella, Roberto et al

in IEEE Transaction on Reliability (2019)

The reliability of mobile devices is a challenge for vendors since the mobile software stack has significantly grown in complexity. In this article, we study how to assess the impact of faults on the ... [more ▼]

The reliability of mobile devices is a challenge for vendors since the mobile software stack has significantly grown in complexity. In this article, we study how to assess the impact of faults on the quality of user experience in the Android mobile OS through fault injection. We first address the problem of identifying a realistic fault model for the Android OS, by providing developers a set of lightweight and systematic guidelines for fault modeling. Then, we present an extensible fault injection tool (AndroFIT) to apply such fault model on actual, commercial Android devices. Finally, we present a large fault injection experimentation on three Android products from major vendors and point out several reliability issues and opportunities for improving the Android OS. [less ▲]

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See detailEvolutionary Fuzzing of Android OS Vendor System Services
Iannillo, Antonio Ken UL; Natella, Roberto; Cotroneo, Domenico

in Empirical Software Engineering (2019)

Android devices are shipped in several flavors by more than 100 manufacturer partners, which extend the Android “vanilla” OS with new system services and modify the existing ones. These proprietary ... [more ▼]

Android devices are shipped in several flavors by more than 100 manufacturer partners, which extend the Android “vanilla” OS with new system services and modify the existing ones. These proprietary extensions expose Android devices to reliability and security issues. In this paper, we propose a coverage-guided fuzzing platform (Chizpurfle) based on evolutionary algorithms to test proprietary Android system services. A key feature of this platform is the ability to profile coverage on the actual, unmodified Android device, by taking advantage of dynamic binary re-writing techniques. We applied this solution to three high-end commercial Android smartphones. The results confirmed that evolutionary fuzzing is able to test Android OS system services more efficiently than blind fuzzing. Furthermore, we evaluate the impact of different choices for the fitness function and selection algorithm. [less ▲]

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See detailAnalyzing the Context of Bug-Fixing Changes in the OpenStack Cloud Computing Platform
Cotroneo, Domenico; De Simone, Luigi; Iannillo, Antonio Ken UL et al

in 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE) (2019)

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