A large part of microprocessor cores in use today are de- signed to be cheap and mass produced. The diagnostic process, which is fundamental to improve yield, has to be as cost effective as possible. This paper presents a novel approach to the construction of diagnosis-oriented software-based test sets for microprocessors. The methodology exploits existing manufacturing test sets designed for software-based self-test and improves them by using a new diagnosis-oriented approach. Experimental results are reported in this paper showing the feasibility, robustness, and effectiveness of the approach for diagnosing stuck-at faults on an Intel i8051 processor core.

An Effective technique for the Automatic Generation of Diagnosis-oriented Programs for Processor Cores / Bernardi, Paolo; SANCHEZ SANCHEZ, EDGAR ERNESTO; Schillaci, Massimiliano; Squillero, Giovanni; SONZA REORDA, Matteo. - In: IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS. - ISSN 0278-0070. - 27:(2008), pp. 570-574. [10.1109/TCAD.2008.915541]

An Effective technique for the Automatic Generation of Diagnosis-oriented Programs for Processor Cores

BERNARDI, PAOLO;SANCHEZ SANCHEZ, EDGAR ERNESTO;SCHILLACI, MASSIMILIANO;SQUILLERO, Giovanni;SONZA REORDA, Matteo
2008

Abstract

A large part of microprocessor cores in use today are de- signed to be cheap and mass produced. The diagnostic process, which is fundamental to improve yield, has to be as cost effective as possible. This paper presents a novel approach to the construction of diagnosis-oriented software-based test sets for microprocessors. The methodology exploits existing manufacturing test sets designed for software-based self-test and improves them by using a new diagnosis-oriented approach. Experimental results are reported in this paper showing the feasibility, robustness, and effectiveness of the approach for diagnosing stuck-at faults on an Intel i8051 processor core.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1831333
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