A Novel Test Generation Methodology for Adaptive Diagnosis
ABSTRACT This paper presents a automatic test pattern generation technique to improve the diagnostic resolution of a given test set. Each test pattern generated by existing techniques detects a large number of faults. Identifying the faulty candidate from a large set of possible fault candidates is extremely difficult and time consuming. A novel framework to adoptively generate additional patterns for diagnosing the faulty location is presented. The additional patterns prune a set of fault free candidates from the possible fault candidates. The proposed technique improves the diagnostic resolution where each new pattern detects only a small number of faults and each fault is detected by few patterns. The proposed method is applicable to any fault model and distinguishes a large number of faults with a small number of patterns. For simplicity we demonstrate the effectiveness of the approach on the path delay fault model.
Conference Paper: Improving fault diagnosis accuracy by automatic test set modification[Show abstract] [Hide abstract]
ABSTRACT: Fault diagnosis is the task of identifying a faulty component in a complex system using data collecting from a test section. Diagnostic resolution, that is the ability to discriminate a faulty component in a set of possible candidates, is a property that the system model must expose to provide accuracy and robustness in the diagnosis. Such a property depends on the selection of an appropriate test set capable to provide a unique interpretation of the test outcomes. In this paper a quantitative metric for the evaluation of diagnostic resolution of a test set is proposed, together with an algorithm for the minimal extension of a given test set in order to provide a complete discrimination of failures affecting a system, to be used as a support for analysts during the definition of a testing framework.Test Conference (ITC), 2010 IEEE International; 12/2010