In a previous paper the authors applied the Abstract Interpretation approach for approximating the probabilistic semantics of biological systems, modeled specifically using the Chemical Ground Form calculus.
The methodology is based on the idea of representing a set of experiments, which differ only for the initial concentrations, by abstracting
the multiplicity of reagents present in a solution,
using intervals. In this paper, we refine the approach in order to address probabilistic termination properties.
More in details, we introduce a refinement of the abstract LTS semantics and we abstract
the probabilistic semantics using a variant of Interval Markov Chains.
The abstract probabilistic model
safely approximates a set of concrete experiments and reports conservative lower and upper bounds for probabilistic termination.