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International audience; The complexity of cell phones is continually increasing, with regards to both hardware and software parts. As many complex devices, their components are usually designed and verified separately by specialized teams of engineers and programmers. However, even if each isolated part is working flawlessly, it often happens that bugs in one software application arise due to the interaction with other modules. Those software misbehaviors become particularly critical when they affect the residual battery life, causing power dissipation. An automatic approach to detect power-affecting software defects is proposed. The approach is intended to be part of a qualifying verification plan and complete human expertise. Motorola, always at the forefront of researching innovations in the product development chain, experimented the approach on a mobile phone prototype during a partnership with Politecnico di Torino. Software errors unrevealed by all human-designed tests have been detected by the proposed framework, two out of three critical from the power consumption point of view, thus enabling Motorola to further improve its verification plans. Details of the tests and experimental results are presented.

International audience; Mobile phones are becoming more and more complex devices, both from the hardware and from the software point of view. Consequently, their various parts are often developed separately. Each sub-system or application may be worked out by a specialized team of engineers and programmers. Frequently, bugs in one component are triggered by the complex interaction between the different applications. Those errors sometimes lead to power dissipation and other misbehaviors that lower residual battery life, a catastrophic event from the user perspective. In this paper we propose a model-based automatic approach to uncover software bugs, which is intended to complement human expertise and complete a qualifying verification plan. The system has been applied on the prototype of a Motorola mobile phone during a partnership with Politecnico di Torino. We demonstrate that our approach is effective by detecting three distinct software misbehaviours that escape all traditional tests. The paper details the methodology, tests and results.