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Among various abstract domains, the interval domain is simple but also less precise. To improve the precision of static defect detection based on the interval domain, we propose a symbolic three-valued logic (STVL) based interval analysis. Our STVL differs from other symbolic techniques in that it is capable of handling the logical relationship between variables, which could help eliminating false positives. In addition, for the pointer related defect detection, we introduce a STVL-based pointer model, which naturally supports the pointer arithmetic operation, alias analysis and point-to memory abstraction. Moreover, we present a unified symbolic procedure summary model, also STVL-based, to extract the call effect of each invocation and achieve context-sensitivity. Experimental results indicate that the technique is able to achieve sizable precision improvements at reasonable costs, compared with the none-symbolic method.

Theoretically, metal Sn owns higher initial coulombic efficiency than SnO2 in the sodium‐ion batteries (SIBs). Metal Sn is commonly obtained by the thermal reduction of SnO2 at present. However, the uncontrollable growth of metal Sn particles during the reduction progress is a key challenge. In this work, a composite material of refined metal Sn particles (particle size about 20∼200 nm) and carbon buffer medium has been prepared by a novel method, which is simple thermal reduction adopted after the treatment of SnO2/RGO in the pitch kerosene solution. The results show that this method overcomes the uncontrollable growth of metal Sn particles. Electrochemical tests show that C/Sn/RGO possesses a higher initial reversible capacity of 476.2 mAh g−1, and a higher initial coulombic efficiency of 70.3%. This method would have wider applications for the attractive properties of Na‐ion batteries in the future.

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