Abstract: An automated analysis system that identifies detectability problems, diagnosability problems, and possible ways to change rank order of diagnoses in a diagnostic system and makes the problems and possible improvements visible to test programmers to aid in test improvement. Components that have no coverage and components that have inadequate coverage (according to a heuristic criteria) are identified as potential detectability problems. Components that are exercised by identical operations in all tests are identified as diagnosability problems. If an incorrect diagnosis is made, the automated analysis system identifies failing tests that have no coverage of any component in the true failure cause. In addition, if an incorrect diagnosis is made, the automated analysis system identifies ways of changing the rank order of diagnoses, including coverages that can be reduced and identification of operation violations that can be eliminated or deliberately added.

Abstract: A method is described which increases the diagnostic resolution of a fault dictionary 130 used by automated test equipment (ATE) to determine a failed device in a unit under test 120. To achieve the goal of better diagnostic resolution, the method of the present invention first uses a combination of strategies to generate different fault syndromes. If all generated fault syndromes are not the same, then only "possible" fault detection data in the fault dictionary 130 is then used to analyze the syndromes. If all fault syndromes are the same, then only "hard" detection data in the fault dictionary is used to analyze the fault syndromes. Fault resolution is increased by treating the two categories of detection data separately, because there are fewer possible faults in each category than in the situation wherein both fault types are merged.

Abstract: Disclosed is a method for compressing sequences of data-vectors, which sequences are to be used for testing circuit boards with the aid of a circuit board testing machine. The method involves an initial compression of the data-vector sequence followed by a so-called K-T transformation of the remaining data-vectors. The initial compression involves eliminating redundant data-vectors from the initial sequence and retaining only the unique data-vectors together with sequencing information indicating where in the initial sequence each unique-data vector occurred. The K-T transformation involves a bitwise logical exclusive-OR operation (XOR) whereby the remaining data-vector sequence is K-T transformed thereby further compressing the sequence without losing any of the original sequence information.