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Extra resources for 13.Computer-Aided Design of Integrated Circuits
Fault dictionaries store output information, produced by the circuit under consideration, on application of the given set of test vectors and under the influence of the set of modeled faults. In contrast, dynamic (effect–cause) diagnosis techniques detect the faulty behavior of the circuit while the test set is applied (34–40). Recent trends show the increasing popularity of integrated diagnosis techniques in which the focus is on using small amounts of precomputed information and coupling this with efficient dynamic algorithms to perform fault location (31,41).
Techniques for handling situations when the faulty responses do not match with any of the stored responses (exactly) are discussed later in this article under the section Unmodeled Fault Diagnosis. Since fault dictionaries are typically prohibitively large to store, fault-dictionary compaction has been an important focus of research. Past work addressing the size problem has yielded solutions in two distinct directions. The first set of contributions provide fault-dictionary compaction targeting high modeled fault resolution (25,29–32), while the second set offers alternative representations for storing the full fault dictionary (30,31,33).
368–370. 27. J. Richman and K. R. Bowden, The modern fault dictionary, Proc. Int. , 1985, pp. 696–702. 28. V. Ratford and P. Keating, Integrating guided probe and fault dictionary: An enhanced diagnostic approach, Proc. Int. , 1986, pp. 304–311. 29. I. Pomeranz and S. M. Reddy, On the generation of small dictionaries for fault location, Proc. IEEE Int. Conf. -Aided Des. (ICCAD ’92), 1992, pp. 272–279. 30. P. G. Ryan, W. K. Fuchs, and I. Pomeranz, Fault dictionary compression and equivalence class computation for sequential circuits, Proc.