The integrated circuits design flow is rapidly moving towards higher description levels. However, test-related activities are lacking behind this trend, mainly since effective fault models and test signals generators are still missing. This paper proposes ARPIA, a new simulation-based evolutionary test generator. ARPIA adopts an innovative high-level fault model that enables efficient fault simulation and guarantees good correlation with gate-level results. The approach exploits an evolutionary algorithm to drive the search of effective patterns within the gigantic space of all possible signal sequences. ARPIA operates on register-transfer level VHDL descriptions and generates effective test patterns. Experimental results show that the achieved results are comparable or better than those obtained by high-level similar approaches or even by gate-level ones.

ARPIA: a High-Level Evolutionary Test Signal Generator / Corno, Fulvio; Cumani, G; SONZA REORDA, Matteo; Squillero, Giovanni. - 2037:(2001), pp. 298-306. ((Intervento presentato al convegno EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM tenutosi a Como (ITA) nel April 18–20, 2001 [10.1007/3-540-45365-2_31].

ARPIA: a High-Level Evolutionary Test Signal Generator

CORNO, Fulvio;SONZA REORDA, Matteo;SQUILLERO, Giovanni
2001

Abstract

The integrated circuits design flow is rapidly moving towards higher description levels. However, test-related activities are lacking behind this trend, mainly since effective fault models and test signals generators are still missing. This paper proposes ARPIA, a new simulation-based evolutionary test generator. ARPIA adopts an innovative high-level fault model that enables efficient fault simulation and guarantees good correlation with gate-level results. The approach exploits an evolutionary algorithm to drive the search of effective patterns within the gigantic space of all possible signal sequences. ARPIA operates on register-transfer level VHDL descriptions and generates effective test patterns. Experimental results show that the achieved results are comparable or better than those obtained by high-level similar approaches or even by gate-level ones.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/1501661
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