With the complexity of nanoelectronic devices rapidly increasing, an efficient way to handle large number of embedded instruments became a necessity. The IEEE 1687 standard was introduced to provide flexibility in accessing and controlling such instrumentation through a reconfigurable scan chain. Nowadays, together with testing the system for defects that may affect the scan chains themselves, the diagnosis of such faults is also important. This article proposes a method for generating stimuli to precisely identify permanent high-level faults in a IEEE 1687 reconfigurable scan chain: the system is modeled as a finite state automaton where faults correspond to multiple incorrect transitions; then, a dynamic greedy algorithm is used to select a sequence of inputs able to distinguish between all possible faults. Experimental results on the widely-adopted ITC'02 and ITC'16 benchmark suites, as well as on synthetically generated circuits, clearly demonstrate the applicability and effectiveness of the proposed approach: generated sequences are two orders of magnitude shorter compared to previous methodologies, while the computational resources required remain acceptable even for larger benchmarks.

A Novel Sequence Generation Approach to Diagnose Faults in Reconfigurable Scan Networks / Cantoro, Riccardo; Damljanovic, Aleksa; Sonza Reorda, Matteo; Squillero, Giovanni. - In: IEEE TRANSACTIONS ON COMPUTERS. - ISSN 0018-9340. - ELETTRONICO. - 69:1(2020), pp. 87-98. [10.1109/TC.2019.2939125]

A Novel Sequence Generation Approach to Diagnose Faults in Reconfigurable Scan Networks

Cantoro, Riccardo;Damljanovic, Aleksa;Sonza Reorda, Matteo;Squillero, Giovanni
2020

Abstract

With the complexity of nanoelectronic devices rapidly increasing, an efficient way to handle large number of embedded instruments became a necessity. The IEEE 1687 standard was introduced to provide flexibility in accessing and controlling such instrumentation through a reconfigurable scan chain. Nowadays, together with testing the system for defects that may affect the scan chains themselves, the diagnosis of such faults is also important. This article proposes a method for generating stimuli to precisely identify permanent high-level faults in a IEEE 1687 reconfigurable scan chain: the system is modeled as a finite state automaton where faults correspond to multiple incorrect transitions; then, a dynamic greedy algorithm is used to select a sequence of inputs able to distinguish between all possible faults. Experimental results on the widely-adopted ITC'02 and ITC'16 benchmark suites, as well as on synthetically generated circuits, clearly demonstrate the applicability and effectiveness of the proposed approach: generated sequences are two orders of magnitude shorter compared to previous methodologies, while the computational resources required remain acceptable even for larger benchmarks.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2751534