Programmers regularly explore the execution of code examples to verify assumptions by adding print statements or commenting in and out setup code in their implementation to isolate code paths of interest. In our formative study on developing embedded programs, where proximity to hardware dictates low abstraction levels, we observed that wrong assumptions occur frequently. However, traditional editors for embedded programs lack support for such explorations. Consequently, programmers have to re-create and clean up setup and print statements in their code for each example.

We present Kerfmeter, a hardware + software device that automatically determines how much material the laser cutter burns off, also known as kerf. Its knowledge about kerf allows Kerfmeter to make the joints of laser cut 3D models fit together with just the right tension, i.e., loose enough to allow for comfortable assembly, yet tight enough to hold parts together without glue—all this without user interaction. Kerfmeter attaches to the head of a laser cutter and works as follows: when users send a model to the laser cutter, Kerfmeter intercepts the job, injects a brief calibration routine that determines kerf, dilates the cutting plan according to this kerf, and then proceeds to fabricate the cutting plan. During the calibration routine, Kerfmeter cuts a 2cm Archimedean spiral and uses a motor to rotate it in place until it jams against the surrounding material; the angle at which the spiral jams allows Kerfmeter to infer kerf. The calibration process takes about 20s, which is >10x faster than traditional, manual kerf calibration, while also eliminating the need for expertise. In our technical evaluation, Kerfmeter produced functioning press fit joints reliably at a precision comparable to traditional manual kerf strips. Kerfmeter makes it easy to sample repeatedly; we demonstrate how this allows boosting precision past any traditional kerf strip.