On improving efficiency of model checking through systematically ...

this case study is a very good example to test the capability of our transformation
tool.
This case study is classified as small in physical size. The state space is
infinite because of the increment of Integer variables.
4.5 Summary
This chapter introduced four case-studies that are used to evaluate our approach
for improving efficiency of model checking through systematically
combining Nbac and PMC/Uppaal.
We choose case studies so that we can evaluate the technique at different
typical models. Although the ultimate goal is the verification of huge and
infinite models, simpler models will help to characterize the effect of factors
such as size, state space, etc. on verification.
The characteristic of four case studies are summerized in Table 4.1 and
4.2. Table 4.1 gives a general view about the characteristic of those casestudies.
Table 4.2 presents the physical size of those systems in terms of the
number of locations, transitions, Boolean operations and variables.
Table 4.1: System characteristics
System Physical size State space
Tiny example small infinite-variable
Asynchronous reader/writer alg. large finite
Fischer’s protocol small infinite-realtime
Subway system small infinite-variable
Nbac is able to generate several different abstract models of a system.
Table 4.2 shows a few abstract models distinguished by the number of locations
for every system . Fischer-2 means that the system is of the Fischer’s
protocol that consists of two processes. Subway-2-p1 means that the system
is of a subway system that consists of two subways and the property to
verify is property 1. Subway-2-p2 is the model for which Uppaal could not
even initialize the data structure since memory was exhausted.
An observation on Table 4.2 shows that there is no environment factor
in the Tiny example and the Asynchronous reader/writer algorithm. In
addition, the number of Boolean operators applied in the Asynchronous
reader/writer algorithm is very large (more than 20000) in compared with
other models. We expect that these features could affect the verification
performance.
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