A general method is proposed to automatically generate a DfT solution aiming at the detection of catastrophic faults in analog and mixed-signal integrated circuits. The approach consists in modifying the topology of the circuit by pulling up (down) nodes and then probing differentiating node voltages. The method generates a set of optimal hardware implementations addressing the multi-objective problem such that the fault coverage is maximized and the silicon overhead is minimized. The new method was applied to a real-case industrial circuit, demonstrating a nearly 100 percent coverage at the expense of an area increase of about 5 percent.
Automatic generation of test infrastructures for analog integrated circuits by controllability and observability co-optimizationVLSI, the integration, vol 55, p. 393-400.
The detection level of defects in today's mixedsignal ICs lags behind the extremely high demand of industries such as automotive. This is mainly because analog blocks in these ICs have high test escape rates as a result of the typical testing based on the performance specifications. Defect-oriented techniques have been proposed to solve the problem of this poor fault coverage for analog circuits. Their effectiveness in practice is however still limited due to the inadequate fault models used to represent physical failures. This paper presents a new open-gate DC fault model. Experimental results on fabricated test circuits in 0.35µm BCD technology are used to validate the proposed fault model and the commonly used high-value-resistance model. Finally, a new testing approach to detect the corresponding open defects in analog circuits is discussed, which is based on forcing the transistors outside their designed operation region.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.