Consistency in dataflow graphs

Analytical properties of programming languages with dataflow graph semantics are discussed. It is shown that one of the most serious problems with these languages is that subtle inconsistencies between parts of the dataflow graph can be inadvertently created. These inconsistencies can lead to deadlock, or in the case of nonterminating programs, to unbounded memory requirements. Consistency is defined to mean that the same number of tokens is consumed as produced on any arc, in the long run. A token-flow model is developed for testing for inconsistency. The method is a generalization of consistency checks for synchronous dataflow (SDF) graphs. The token-flow model is compared to similar tests applied to hybrid dynamical systems. It is argued that dataflow semantics make steady-state analysis possible, leading to a simpler method in most cases