In this study, we propose a low-cost approach to error detection for arithmetic orientated data paths by performing lightweight shadow computations in modulo-3 space for each main computation. By leveraging the binding and scheduling flexibility of high-level synthesis, we detect errors through diverse binding and minimize area cost through intelligent checkpoint scheduling and modulo-3 reducer sharing. We evaluated our technique with 12 high-level synthesis benchmarks using FPGA emulated netlist-level error injection. We observe coverages of 99.13% for stuck-at faults, 99.46% for soft errors, and 99.67% for timing errors with a 25.7% area cost and negligible performance impact. Leveraging error detection latencies on the order of 10 cycles (3 orders of magnitude faster than end result check) for soft errors, we also explore a rollback recovery method with an additional area cost of 28.0%, observing a 175x increase in reliability against soft errors.