Integrated sensing and communication (ISAC) is a cornerstone for future sixth-generation (6G) networks, enabling simultaneous connectivity and environmental awareness. However, practical realization faces significant challenges, including residual self-interference (SI) in full-duplex (FD) systems and performance degradation of short-packet transmissions under finite blocklength (FBL) constraints. This work studies a reconfigurable intelligent surface (RIS)-assisted FD ISAC system serving multiple downlink users while tracking a moving target, explicitly accounting for SI and FBL effects in both communication and sensing. We formulate an optimization framework to minimize service adaptation gaps while ensuring sensing reliability, solved via alternating optimization and successive convex approximation. Numerical results show that short blocklengths enable fast adaptation but increase radar outage due to fewer pulses and motion sensitivity, whereas longer blocklengths improve SINR and reduce outages but allow target motion to degrade sensing. A regime-dependent "sweet spot" emerges, where blocklength and beamformer allocation jointly balance throughput and sensing, with HD favored at very short blocklengths and FD at longer blocklengths. RIS-assisted optimization expands the FD-operating regime, enabling reliable communication and radar sensing at lower blocklengths.

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