Testing is a key issue in the design and production of digital circuits: the adoption of BIST (Built-in Self-Test) techniques is increasingly popular, but sometimes requires efficient algorithms for the automatic generation of the logic which generates the test vectors applied to the unit under test. This paper addresses the issue of identifying a cellular automaton able to generate input patterns to detect stuck-at faults inside a finite state machine (FSM). A suitable hardware structure is first identified. A genetic algorithm is then proposed, which directly identifies a cellular automaton able to reach a very good fault coverage of the stuck-at faults. The novelty of the method consists in combining the generation of test patterns with the synthesis of a cellular automaton able to reproduce them. Experimental results are provided, which show that in most of the standard benchmark circuits the cellular automaton selected by the genetic algorithm is able to reach a fault coverage close to the maximum one. Our approach is the first attempt of exploiting evolutionary techniques for identifying the hardware for input pattern generation in BIST structures.

A genetic algorithm for automatic generation of test logic for digital circuits / Corno, Fulvio; Prinetto, Paolo Ernesto; SONZA REORDA, Matteo;  ,. - STAMPA. - (1996), pp. 10-16. ((Intervento presentato al convegno ICTAI 1996 : 8th IEEE International Conference on Tools with Artificial Intelligence, 1996 tenutosi a Toulouse (France) nel Nov 16-19, 1996 [10.1109/TAI.1996.560394].

A genetic algorithm for automatic generation of test logic for digital circuits

CORNO, Fulvio;PRINETTO, Paolo Ernesto;SONZA REORDA, Matteo;
1996

Abstract

Testing is a key issue in the design and production of digital circuits: the adoption of BIST (Built-in Self-Test) techniques is increasingly popular, but sometimes requires efficient algorithms for the automatic generation of the logic which generates the test vectors applied to the unit under test. This paper addresses the issue of identifying a cellular automaton able to generate input patterns to detect stuck-at faults inside a finite state machine (FSM). A suitable hardware structure is first identified. A genetic algorithm is then proposed, which directly identifies a cellular automaton able to reach a very good fault coverage of the stuck-at faults. The novelty of the method consists in combining the generation of test patterns with the synthesis of a cellular automaton able to reproduce them. Experimental results are provided, which show that in most of the standard benchmark circuits the cellular automaton selected by the genetic algorithm is able to reach a fault coverage close to the maximum one. Our approach is the first attempt of exploiting evolutionary techniques for identifying the hardware for input pattern generation in BIST structures.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2501271
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo