Automatic testing environment for multi-core embedded software—ATEMES

Software testing during the development process of embedded software is not only complex, but also the heart of quality control. Multi-core embedded software testing faces even more challenges. Major issues include: (1) how demanding efforts and repetitive tedious actions can be reduced; (2) how resource restraints of embedded system platform such as temporal and memory capacity can be tackled; (3) how embedded software parallelism degree can be controlled to empower multi-core CPU computing capacity; (4) how analysis is exercised to ensure sufficient coverage test of embedded software; (5) how to do data synchronization to address issues such as race conditions in the interrupt driven multi-core embedded system; (6) high level reliability testing to ensure customer satisfaction. To address these issues, this study develops an automatic testing environment for multi-core embedded software (ATEMES). Based on the automatic mechanism, the system can parse source code, instrument source code, generate testing programs for test case and test driver, support generating primitive, structure and object types of test input data, multi-round cross-testing, and visualize testing results. To both reduce test engineer's burden and enhance his efficiency when embedded software testing is in process, this system developed automatic testing functions including unit testing, coverage testing, multi-core performance monitoring. Moreover, ATEMES can perform automatic multi-round cross-testing benchmark testing on multi-core embedded platform for parallel programs adopting Intel TBB library to recommend optimized parallel parameters such as pipeline tokens. Using ATEMES on the ARM11 multi-core platform to conduct testing experiments, the results show that our constructed testing environment is effective, and can reduce burdens of test engineer, and can enhance efficiency of testing task.     

TiO2-based microsphere with large pores to improve the electrochemical performance of Li-ion anodes

A microsphere composed of nano-TiO₂ and carbon with a large pore size was constructed, and its potential as the anode active material for lithium-ion batteries was explored. The pores can promote the intake of the liquid electrolyte by the microsphere, improving the transport of electrons and ions, and the carbon surrounding the nano-TiO₂ in the skeleton of the microsphere can decrease the electronic resistance. At low charge/discharge rates of 0.5–2C, the cell made of the porous microspheres exhibited better stability of capacity—from low capacity retention of less than 70% to greater than 88% after 200 cycles—than the cell made of the as-received nano-TiO₂. At high rates of 5–10C, the capacity of the cell made of the as-received nano-TiO₂ was contributed mainly by the capacitance effect. In contrast, the capacity of the cell made of the porous microspheres was contributed mainly by the electrochemical lithiation/delithiation, resulting in a higher capacity with good stability for at least 1000 cycles.     

Cloud evidence tracks of storage service linking with iOS systems

The increasing usage of mobile cloud computing leads the cloud to become a hotbed of crime. Cloud storage is different from previous data storage in digital forensics. In this paper, we concentrate on gathering evidence from mobile iOS devices and the types of data remnants that can be found on iOS devices for different user scenarios and device states. We develop several steps for experimenting on Google Drive, OneDrive and Dropbox. We found that the evidence collection of power-off state is not the major problem in digital forensics. Different applications of cloud storage show the different statuses of data remnants. The study also shows that thumbnails and cache files are the key of evidence recovery. We present how the digital investigators to collect evidence by examining the data remnants files as well.