SLIME: State Learning in the Middle of Everything for Tool-Assisted Vulnerability Detection

Behavioural state machine models of software systems are a valuable tool for validating behaviour, but creating state machine models of existing implementations manually is highly undesirable. Fortunately, automata learning frameworks exist that completely automate the critical aspect of automata learning. However, some manual setup is usually required outside of the critical learning algorithm to create a test harness into which the system …