Abstract: A method includes receiving a set of execution paths for a directed acyclic graph. The directed acyclic graph includes multiple nodes and multiple edges. The nodes include sets of executable code. The edges represent an operational relationship between at least two nodes. The execution paths include a subset of the nodes connected by a sequence of edges. The method further includes setting a current training level to a maximum training level. The method further includes constructing a transition probability set for the current training level and adding the transition probability set to a transition probability dictionary. The method further includes storing the transition probability dictionary as a final transition probability dictionary.

Abstract: A method including setting an initial lookback path length for a current path in a directed acyclic graph. The current path includes a subset of the nodes connected by a sequence of the edges. The method also includes querying, for a current lookback path length, whether a matching key is present in a transition probability dictionary (TPD). The method also includes querying, responsive to the matching key being present in the TPD for the current lookback path length, whether a matching value is present for the matching key. The matching value includes a sample path in the TPD that matches the current path. Responsive to the matching value being present in the TPD for the matching key, a next node associated with the matching value is returned. The next node is connectable in a valid operational relationship to a last node in the current path.