Intelligible TinyOS Sensor Systems: Explanations for Embedded Software

As embedded sensing systems are central to developing pervasive, context-aware services, the applications running on these systems should be intelligible to system programmers and to users. Given that sensor systems are programmed in low-level languages, manually writing high-level explanations about their decision model requires knowledge about the system architecture, and is error-prone. We explore the possibility of extracting explanations which are small and expressive, but still preserve bit-level accuracy when needed. We contribute a tool which automatically and soundly generates compact, graphical explanations from sensor software implementation at compile-time. We base our algorithm on the techniques of (i) finite-state machine model extraction from software as used in model checking, and (ii) abstraction of program execution traces. We experiment with extracting explanations from heavyweight, low-level TinyOS applications for a mainstream sensor platform.