By Xuandong Li, Zhiming Liu, Wang Yi
This booklet constitutes the refereed lawsuits of the 1st overseas Symposium on responsible software program Engineering: Theories, instruments, and functions, SETTA 2015, held in Nanjing, China, in November 2015.
The 20 complete papers offered including three invited talks have been rigorously reviewed and chosen from 60 submissions.The papers are prepared on topical sections on probabilistic platforms; hybrid and cyber-physical platforms; trying out, simulation and inference; bisimulation and correctness; layout and implementation; symbolic execution and invariants; and verification and case studies.
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Additional info for Dependable Software Engineering: Theories, Tools, and Applications: First International Symposium, SETTA 2015, Nanjing, China, November 4-6, 2015, Proceedings
Time in Stochastic Games and Markov Automata 31 Table 2. 201 Table 3. 039 Table 4. 000 in Table 4). For homogeneous costs we can observe a similar eﬀect as for DPMS and PS: The number of processors inﬂuences the number of states in the system, but has a negligible impact on the reachability. The latter is completely determined by the number of jobs. What’s more, the minimum and the maximum 32 H. Hateﬁ et al. reachability are the same in this case. These eﬀects vanish if we assume heterogeneous costs.
For this, on the one hand, we construct the ﬁxed point characterisation of the transformed game using Theorem 1 by assigning the constant cost of one to all Markovian transitions. On the other 28 H. Hateﬁ et al. hand, we reinterpret the representation of the ﬁxed point characterisation of the original model by a series of sound variable substitutions, partly inspired by the transformation. At the end we conclude that both of the ﬁxed point characterisations are the same, and thereby their least ﬁxed points are exactly equal.
Then the rewards of the ﬁve transitions after transformation are shown in Fig. 2(b). The Markovian transitions tr1 , tr2 , and tr5 are modiﬁed as follows. Transitions tr3 and tr4 remain unchanged as they are probabilistic. The expected residence time before taking tr1 is scaled such that it matches the expected cost in the original game, i. e. the new exit rate becomes λtr1 /c(tr1 ) = 10/5 = 2. The transient reward rate is adjusted accordingly and becomes ρt (tr1 )/c(tr1 ) = 1/5. The instantaneous reward does not change.