Battery-free devices enable sensing in hard-to-access locations, opening up new opportunities in various fields such as healthcare, space, or civil engineering. Such devices harvest ambient energy and store it in a capacitor. Due to the unpredictable nature of the harvested energy, a power failure can occur at any time, resulting in a loss of all non-persistent information (\textit{e}.\textit{g}., processor registers, data stored in volatile memory). Checkpointing volatile data in non-volatile memory allows the system to recover after a power failure, but raises two issues: (i) spatial and temporal placement of checkpoints; (ii) memory allocation of variables between volatile and non-volatile memory, with the overall objective of using energy as efficiently as possible.

While many techniques rely on the developer to address these issues, we present \textsc{SCHEMATIC}, a compiler technique that automates checkpoint placement and memory allocation to minimize the overall energy consumption. \textsc{SCHEMATIC} ensures that programs will eventually terminate (\emph{forward progress} property). Moreover, checkpoint placement and memory allocation adapt to the size of the energy buffer and the capacity of volatile memory.
\textsc{SCHEMATIC} takes advantage of volatile memory (VM) to reduce the energy consumed, by automatically placing the most used variables in VM.

We tested \textsc{SCHEMATIC} for different experimental settings (size of volatile memory and capacitor) and results show an average energy reduction of 51,% compared to related techniques.