Both increases in the absolute number of elderly persons and in their longevity will increase future Medicare expenditures. Yet, the expected increase in per person health care expenditures caused by greater longevity of Medicare beneficiaries will be less than expected because of the concentration of expenditures at the end of life rather than during extra years of a relatively healthy life. The latter conclusion may be altered, however, because of other underlying considerations, such as technological change.
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.
This paper presents a new path sensitive algorithm for static defect detecting running in polynomial time. In this method, property state conditions are represented by abstract domain of variables, and infeasible paths can be identified when some variables' abstract value range is empty. This method avoids the combination explosion of full path analysis by merging the conditions of identical property state at join points in the CFG (control flow graph). This algorithm has been implemented as part of a defect testing tool called DTS (defect testing system).Practical test results show that this method can reduce false positive.
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