By Markus Müller-Olm, Helmut Seidl
This booklet constitutes the completely refereed court cases of the twenty first overseas Symposium on Static research, SAS 2014, held in Munich, Germany, in September 2014. The 20 revised complete papers have been chosen from fifty three submissions and are offered including three invited talks. The papers deal with all elements of static research, together with summary interpretation, summary checking out, malicious program detection, info circulate research, version checking, application transformation, application verification, safety research, and kind checking.
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Extra info for Static Analysis: 21st International Symposium, SAS 2014, Munich, Germany, September 11-13, 2014. Proceedings
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Then, C c (i)|o1 :q = i and C c (i)|o2 :q = i−1. Let us assume that the same cost analyzer has been used to approximate C and C c , and that the analysis assumed the worst-case cost of m for all instances of m. Then, we can gain precision by obtaining the cost as C(x)|o:m = C(x)|o:m /C c (x)|o:m if nact(o:m) = 1 and C(x)|o:m = C(x)|o:m , otherwise. Intuitively, when the MHP analysis tells us that there is at most one instance of m (by means of nact) and, under the above assumptions, the division is achieving the desired eﬀect of leaving the cost of one instance only.
We can improve the accuracy as follows. First, we use an instantiation of the cost analysis in Sec. 4 to determine how many instances of tasks running m at o we might have. This can be done by deﬁning function cost in Sec. 4 as follows: cost(inst) = 1 if inst is the entry instruction to a method, and 0 otherwise. We denote by C c (x) the upper bound obtained using such cost model that counts the number of tasks spawned along the execution, and C c (x)|o:m the number of tasks executing m at location o.