Don´t care-based BDD minimization for embedded software

This paper explores the use of don´t cares in software synthesis for embedded systems. Embedded systems have extremely tight real-time and code/data size constraints, that make expensive optimizations desirable. We propose applying BDD minimization techniques in the presence of a don´t care set to synthesize code for extended Finite State Machines from a BDD-based representation of the FSM transition function. The don´t care set can be derived from local analysis (such as unused state codes or don´t care inputs) as well as from external information (such as impossible input patterns). We show experimental results discuss their implications, the interaction between BDD-based minimization and dynamic variable reordering, and propose directions for future work.