Abstract: Systems and methods disclosed include receiving defect data from a test of a semiconductor device comprising a circuit, the circuit comprising a cell, the cell comprising a first input, a second input and an output, and modeling a first plurality of cell defect modes of the cell with a first multiple input transition cell fault model (MTCFM), the cell defect modes associated with a first signal transition on the first input, and a second signal transition on the second input or the output. Systems and method further include correlating the first plurality of cell defect modes to the defect data to produce a probability of each of the first plurality of cell defect modes matching the defect data, and providing, to a user, an indication of each of at least one of the first plurality of cell defect modes having the probability exceeding a defect probability threshold.

Abstract: Various aspects of the disclosed technology relate to techniques of selecting scan cells from state elements for partial scan designs. Signal probability values for logic gates in a circuit design are first determined. Based on the signal probability values, next-state capture probability values for state elements in the circuit design are computed. Based on the next-state capture probability values, scan cells are selected from the state elements. Scan cells may be further selected based on continuously-updated control weight values and observation weight values associated with the state elements.

Abstract: Various aspects of the disclosed technology relate to techniques of selecting scan cells from state elements for partial scan designs. Signal probability values for logic gates in a circuit design are first determined. Based on the signal probability values, next-state capture probability values for state elements in the circuit design are computed. Based on the next-state capture probability values, scan cells are selected from the state elements. Scan cells may be further selected based on continuously-updated control weight values and observation weight values associated with the state elements.

Abstract: Aspects of the invention relate to techniques for diagnosing compound hold-time faults. A profiling-based scan chain diagnosis may be performed on a faulty scan chain to determine observed scan cell failing probability information and one or more faulty segments based on scan pattern test information. Calculated scan cell failing probability information may then be derived. Based on the calculated scan cell failing probability information and the observed scan cell failing probability information, one or more validated faulty segments are verified to have one or more compound hold-time faults. Finally, one or more clock defect suspects may be identified based on information of the one or more validated faulty segments.

Abstract: Scan chain diagnosis techniques are disclosed. Faulty scan chains are modeled and scan patterns are masked to filter out loading-caused failures. By simulating the masked scan patterns, failing probabilities are determined for cells on a faulty scan chain. One or more defective cells are identified based upon the failing probability information. A noise filtering system such as the one based upon adaptive feedback may be adopted for the identification process.

Abstract: Aspects of the invention relate to techniques for diagnosing compound hold-time faults. A profiling-based scan chain diagnosis may be performed on a faulty scan chain to determine observed scan cell failing probability information and one or more faulty segments based on scan pattern test information. Calculated scan cell failing probability information may then be derived. Based on the calculated scan cell failing probability information and the observed scan cell failing probability information, one or more validated faulty segments are verified to have one or more compound hold-time faults. Finally, one or more clock defect suspects may be identified based on information of the one or more validated faulty segments.

Abstract: Scan chain diagnosis techniques are disclosed. Faulty scan chains are modeled and scan patterns are masked to filter out loading-caused failures. By simulating the masked scan patterns, failing probabilities are determined for cells on a faulty scan chain. One or more defective cells are identified based upon the failing probability information. A noise filtering system such as the one based upon adaptive feedback may be adopted for the identification process.