According to one embodiment, an information processing system includes a memory, an inputter, and a processor. The memory stores correlation information including a specification item group, an element item group, and a risk item group. The specification item group includes specification items. The element item group includes element items. The risk item group includes risk items. One of the specification items to be modified is selected by a first operation input to the inputter. One of the element items is selected by a second operation input to the inputter. When the first operation is input, the processor refers to the correlation information and extracts at least one of the element items having a correlation with the one of the specification items. The processor extracts at least one of the risk items having a correlation with one element item of the at least one of the element items selected.

Example test generation systems and methods are described. In one implementation, a hardware test suite generator includes a script reader that receives a test definition script and parses the test definition script. A test generator receives the parsed test definition script from the script reader and creates a test suite. A template reader receives a test definition template and parses the test definition template. A code generator receives the parsed test definition script from the script reader and receives the parsed test definition template from the template reader.

A system and method for monitoring a circuit for impending failure includes measuring changes to frequency-domain impedance with a pair of analog-to-digital converters connected to a conductor while powering up, with or without interposing a series sense resistor for measuring applied current. Changes to frequency-domain impedance or power delivery voltage ratio are identified via a neural network trained to identify frequency-domain impedance associated with normal system behavior and general system failure mode. The neural network may be further trained to produce a predictive probability of specific failure mode types.

An analog-circuit fault diagnosis method based on continuous wavelet analysis and an ELM network comprises: data acquisition: performing data sampling on output responses of an analog circuit respectively through Multisim simulation to obtain an output response data set; feature extraction: performing continuous wavelet analysis by taking the output response data set of the circuit as training and testing data sets respectively to obtain a wavelet time-frequency coefficient matrix, dividing the coefficient matrix into eight sub-matrixes of the same size, and performing singular value decomposition on the sub-matrixes to calculate a Tsallis entropy for each sub-matrix to form feature vectors of corresponding faults; and fault classification: submitting the feature vector of each sample to the ELM network to implement accurate and quick fault classification. The method of the invention has a better effect on extracting the circuit fault features and can be used to implement circuit fault classification accurately and efficiently.

A technique for non-invasively assessing current drawn by a device under test (DUT) by monitoring a supply voltage to the DUT. Frequency data for the DUT may be generated and used to form a current estimation model. First and second voltages are simultaneously measured using first and second test probes electrically connected to the DUT, while the first test probe is connected at a current source, and while the second test probe is connected at a DUT load that is configured to draw current from the current source. The current drawn by the DUT is then assessed by applying the current estimation model to the measured first and second voltages. In one case, the current drawn by the DUT is estimated without insertion of a circuit component into the DUT or extraction of a circuit conductor from the DUT.

Systems and methods of testing the health of vehicular power devices are disclosed herein. A method may include producing operating points as a function of cycling current (I.sub.ds) and voltage drain to source (V.sub.ds) when a subject device is conducting current. The method may further include determining a mean of moving distribution to adapt a center of the moving distribution contrasted with a plurality of known healthy devices. The method may also include indicating an imminent fault in the subject device based upon a discontinuity among operating points above a threshold.

The present application discloses a semiconductor product grading method and grading system. The grading method includes: at the time of an electric property test, classifying the several semiconductor products into a plurality of groups according to several test parameters obtained from the test; carrying out a principal component analysis on the corresponding several test parameters in each group, to obtain eigen parameters for each group; and determining, based on the eigen parameters, grades for the semiconductor products in each group. The semiconductor products in each group are graded through several eigen parameters with similar attributes, so the accuracy of the existing semiconductor product grading is improved and the semiconductor products that meet different customer requirements can be accurately and quickly screened out for shipping.

A device, system, and a computer-implemented method a for identifying an anomaly in an operation of a device includes comparing, by an electrical power analyzer, a current power draw signature of the device with a known power draw signature of the device. There is a determining as to whether at least one anomaly is present in the current power draw signature. A warning is generated in response to determining the at least one anomaly is present in the current power draw signature.

An apparatus for determining a single decision function is configured to obtain measurements from a plurality of devices under test corresponding to stimulating signals applied to the plurality of devices under test. The stimulating signals correspond to a set of tests performed on the plurality of devices under test. The apparatus may further determine a subset of tests from the set of tests, such that the subset of tests is relevant for indicating whether the plurality of devices under test pass the set of tests. The apparatus may also determine the single decision function applicable to measurements from an additional device under test tested using the subset of tests, such that the single decision function is adapted to predict a test result for the set of tests on the basis of the subset of tests.

A computer-implemented method of analyzing an electrical wiring harness assembly comprises receiving, via a processing element, a test result associated with the electrical wiring harness assembly; determining, via the processing element, a probable error type based on the test result; retrieving from a memory element, via the processing element, a plurality of natural language terms associated with the probable error type, each of the plurality of natural language terms having a corresponding phrase order value; and reporting, via a user interface, each of the plurality of natural language terms in an order according to the phrase order values.