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Product cost is a major driver in the consumer electronics market, which is characterized by low profit margins and the use of core-based system-on-chip (SoC) designs. Packaging has been recognized as a significant contributor to the product cost for such SoCs. To reduce packaging cost and the test cost for packaged chips, wafer-level testing (wafer sort) is used in the semiconductor industry to screen defective dies. However, since test time is a major practical constraint for wafer sort, even more so than for package test, not all the scan-based digital tests can be applied to the die under test. We present an optimal test-length selection technique for wafer-level testing of core-based SoCs. This technique, which is based on a combination of statistical yield modeling and integer linear programming, allows us to determine the number of patterns to use for each embedded core during wafer sort such that the probability of screening defective dies is maximized for a given upper limit on the SoC test time. We also present a heuristic method to handle large next-generation SoC designs. Simulation results are presented for five of the ITC'02 SoC Test benchmarks, and the optimal test-length selection approach is compared with the heuristic method.