This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.
Authors:
(1) Pascal Baumann, Max Planck Institute for Software Systems (MPI-SWS), Germany;
(2) Rupak Majumdar, Max Planck Institute for Software Systems (MPI-SWS), Germany;
(3) Ramanathan S. Thinniyam, Max Planck Institute for Software Systems (MPI-SWS), Germany;
(4) Georg Zetzsche, Max Planck Institute for Software Systems (MPI-SWS), Germany.
In this section, we prove Theorem 2.2. The theorem follows easily from previous results for safety verification [Atig et al. 2011; Baumann et al. 2020]. We recall the main ideas as a step toward the more complex proof for fair termination.
Downward Closures: From DCPS to DCFS
The DCFS simulates the downward closure of the DCPS by simulating the composition of the automata for each downward closure. The construction is identical to [Atig et al. 2011, Lemma 5.3]. Thus, we can conclude with the following lemma.
Lemma 3.1. TheK-bounded non-termination problem for DCPS can be reduced in exponential time to the non-termination problem for DCFS. The resulting DCFS is of size at most exponential in the size of the DCPS.
From DCFS Non-Termination to VASS Non-Termination
The 2EXPSPACE upper bound follows by combining Lemmas 3.1, 3.2, and the EXPSPACE upper bound for the non-termination problem for VASS [Rackoff 1978].
The 2EXPSPACE lower bound follows from the observation made already in [Baumann et al. 2020] that the 2EXPSPACE-hardness of K-bounded reachability already holds for terminating DCPS, in which every run is terminating. It is now a simple reduction to take an instance of the 퐾-bounded state reachability problem for a terminating DCPS and add a “gadget” that produces an infinite run whenever the target global state is reached.