Characterization of string-parsing latency as an uncertainty contribution to software timestamping in a virtual measurement system

Abstract In many measurement systems the value delivered by an instrument and the time at which it occurred are transported together as a text protocol line, and both must be recovered by software before entering the measurement result. The accuracy of a measurement depends not only on the measured value but also on the accuracy of its associated timestamp, yet the software parsing that precedes timestamp assignment introduces a variable delay that is rarely treated as a metrological quantity. This paper defines string-parsing latency as an input quantity of the software timestamp and evaluates it according to the GUM. A LabVIEW virtual measurement system, driven by a simulated NI-DAQmx device, realizes two modes: an aggregate per-call benchmark that resolves the intrinsic latency with nanosecond uncertainty, and an end-to-end producer/consumer path that exposes the operating-system contribution. Five parsing methods were characterized over three protocol-string lengths. The per-call latency ranges from 50.3 to 139.6 ns (coverage factor two), with relative standard uncertainty 0.4-1.3 %; the method ranking is statistically unambiguous and every method scales linearly at 0.703 ns per character. The GUM and Monte Carlo intervals agree within 0.03 ns. The parsing contribution is small, metrologically traceable and, on the general-purpose host characterized here and under low processor load, negligible against operating-system jitter; the evaluation methodology, rather than the particular latency values, is the transferable outcome.