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.
|Titolo:||A Novel Sequence Generation Approach to Diagnose Faults in Reconfigurable Scan Networks|
|Data di pubblicazione:||2019|
|Digital Object Identifier (DOI):||10.1109/TC.2019.2939125|
|Appare nelle tipologie:||1.1 Articolo in rivista|