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.
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ABSTRACT: In a two-step defect diagnosis process, a fault detection test set is used for initial diagnosis to compute an initial set of candidate faults. When the initial set is large, diagnostic tests are generated based on the candidate faults in the set, and the set is refined based on the extended test set. This paper investigates the ability of functional broadside tests to serve as diagnostic tests for refining initial sets of candidate faults. The paper discusses the advantages of using functional broadside tests for this purpose. These advantages are related to the fact that the tests create functional operation conditions, and thus avoid nonfunctional effects that may make diagnosis less accurate. It also describes a multistep defect diagnosis process that uses functional broadside tests. Experimental results are presented to show the extent to which functional broadside tests can reduce initial sets of candidate faults.IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 09/2014; 33(9):1429-1433. · 1.20 Impact Factor
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