Active Inference of Extended Finite State Models of Software Systems
Proceedings of 16th edition of the International Conference on Grammatical Inference, PMLR 217:265-269, 2023.
Extended finite state machines (EFSMs) model stateful systems with internal data variables, and have many software engineering applications. It is possible to infer such models by observing system behaviour. Still, existing approaches are either limited to classical FSM models with no internal data state, or implicitly require the ability to reset the system under inference, which may not always be possible. We present an extension to the hW-inference algorithm that can infer EFSM models, with input and output parameters as well as guards and internal registers and their data update functions, from systems without a reliable reset. For the problem to be tractable, we require some assumptions on the observability and determinism of the system. The main restriction is that the control flow of the system must be finite, although data types could be infinite.