TY - GEN
T1 - Optimal on-line built-in self-test structure for system-reliability improvement
AU - Papa, Gregor
AU - Garbolino, Tomasz
PY - 2011
Y1 - 2011
N2 - This paper presents a bio-inspired technique for the generation of a deterministic test pattern generator. In contrast to conventional methods, the proposed evolutionary-based approach reduces the gate count of a built-in self-test structure, which is used for the automatic fault detection. The reduced-gate-count structure is needed to achieve the test structure with a smaller hardware area overhead, while still satisfying the reliability constraints. The presented optimization approach searches concurrently for the optimal combination of the register cells structure, the test patterns order in the generated test sequence, and the bit order of the test patterns. A comparison of the results with similar studies shows the efficiency of the proposed evolutionary approach, which is therefore very useful in the design of robust and fault-tolerant systems, while maintaining the minimum size of the hardware overhead.
AB - This paper presents a bio-inspired technique for the generation of a deterministic test pattern generator. In contrast to conventional methods, the proposed evolutionary-based approach reduces the gate count of a built-in self-test structure, which is used for the automatic fault detection. The reduced-gate-count structure is needed to achieve the test structure with a smaller hardware area overhead, while still satisfying the reliability constraints. The presented optimization approach searches concurrently for the optimal combination of the register cells structure, the test patterns order in the generated test sequence, and the bit order of the test patterns. A comparison of the results with similar studies shows the efficiency of the proposed evolutionary approach, which is therefore very useful in the design of robust and fault-tolerant systems, while maintaining the minimum size of the hardware overhead.
UR - https://www.scopus.com/pages/publications/80051981168
U2 - 10.1109/CEC.2011.5949622
DO - 10.1109/CEC.2011.5949622
M3 - Conference contribution
AN - SCOPUS:80051981168
SN - 9781424478347
T3 - 2011 IEEE Congress of Evolutionary Computation, CEC 2011
SP - 222
EP - 229
BT - 2011 IEEE Congress of Evolutionary Computation, CEC 2011
PB - IEEE Computer Society
ER -