Maximal causality analysis

Perfectly synchronous systems immediately react to the inputs of their environment, which may lead to so-called causality cycles between actions and their trigger conditions. Algorithms to analyze the consistency of such cycles usually extend data types by an additional value to explicitly indicate unknown values. In particular, Boolean functions are thereby extended to ternary functions. However, a Boolean function usually has several ternary extensions, and the result of the causality analysis depends on the chosen ternary extension. In this paper, we show that there always is a maximal ternary extension that allows one to solve as many causality problems as possible. Moreover, we elaborate the relationship to hazard elimination in hardware circuits, and finally show how the maximal ternary extension of a Boolean function can be efficiently computed by means of binary decision diagrams.