A circuit comprises: a bit-flipping signal generation device comprising a storage device and configured to generate a bit-flipping signal based on bit-flipping location information, the storage device configured to store the bit-flipping location information for a first number of bits, the bit-flipping location information obtained through a fault simulation process; a pseudo random test pattern generator configured to generate test patterns based on the bit-flipping signal, the pseudo random test pattern generator comprising a register configured to be a linear finite state machine, the register comprising storage elements and bit-flipping devices, each of the bit-flipping devices coupled to one of the storage elements; and scan chains configured to receive the test patterns, wherein the bit-flipping signal causes one of the bit-flipping devices to invert a bit of the register each time a second number of test patterns is being generated by the pseudo random test pattern generator during a test.

An approach for testing, including a self-test method, a semiconductor chip is disclosed. The approach generates test patterns, including weighted random test patterns, for testing random pattern resistant faults, and un-modeled faults directed at specific logic groups, where the dynamically generated test pattern weights are configured to optimize test coverage and test time. The dynamically generated test patterns are based on factors related to random pattern resistant logic structures interconnected via scan chains. More particularly, the dynamically generated test patterns are designed to enable fault detection within logic structures that are resistant to fault detection when tested with random patterns.

A series of pseudo-random test patterns provide inputs to a logic circuit for performing logic built-in self test (LBIST). A weight configuration module applies one or more weight sets to the pseudo-random test patterns, to generate a series of weighted pseudo-random test patterns. A logic analyzer determines a probability expression for each given net of the logic circuit, based on associated weight sets and a logic function performed by the net. A probability module computes an output probability for each net based on associated probability expressions and associated input probabilities. The weight configuration module optimizes the weight sets, based on the computed net probabilities, and further based on a target probability range bounded by lower and upper cutoff probabilities.

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.

Methods and systems for verifying, via formal verification, a hardware design for a data transformation pipeline comprising one or more data transformation elements that perform a data transformation on one or more inputs, wherein the formal verification is performed under conditions that simplify the data transformations calculations that the formal verification tool has to perform. In one embodiment the hardware design for the data transformation pipeline is verified by formally verifying that the output of an instantiation of the hardware design produces the same output as an instantiation of a hardware design for another data transformation pipeline for a predetermined set of transactions under a constraint that substantially equivalent data transformation elements between the data transformation pipelines produce the same output(s) in response to the same input(s).

The present application relates to a circuit simulation test method and apparatus, a device, and a medium. The method includes: creating a parametric data model, wherein the parametric data model is configured to generate preset write data based on a preset parameter; creating a test platform, wherein the test platform is configured to generate a test result based on the preset write data; creating an eye diagram generation module, wherein the eye diagram generation module is configured to generate a data eye diagram based on the test result; and conducting a simulation test, inputting the preset write data to the test platform and obtaining the test result, and generating the data eye diagram by using the eye diagram generation module.

A test pattern generating method for generating a test pattern for a circuit under test. The test pattern generating method comprises: (a) computing a plurality of signal delay values which a plurality of cells have due to different defects; (b) comparing the signal delay values and signal path delay information of a target circuit to generate a fault model; and (c) generate at least one test pattern according to the fault model.

Techniques facilitating determination and correction of physical circuit event related errors of a hardware design are provided. A system can comprise a memory that stores computer executable components and a processor that executes computer executable components stored in the memory. The computer executable components can comprise a simulation component that injects a fault into a latch and a combination of logic of an emulated hardware design. The fault can be a biased fault injection that can mimic an error caused by a physical circuit event error vulnerability. The computer executable components can also comprise an observation component that determines one or more paths of the emulated hardware design that are vulnerable to physical circuit event related errors based on the biased fault injection.

A delay estimation system estimates a delay of a DUT for an emulation system. The delay estimation system receives logic blocks of the DUT and a combinatorial path connecting one or more of the logic blocks. The system applies a delay model to a feature vector representing the combinatorial path, where the delay model can determine a delay of the combinatorial path. The delay model may be a machine learning model. The system generates a timing graph using the determined delay and provides the timing graph to a compiler to perform placement and routing of the DUT.

A thermal transient response simulation is performed to determine a total thermal resistance value for a structure having a plurality of thermal model elements. A plurality of thermal transient response simulations are also performed for the structure to determine changed total thermal resistance values by varying one of thermal resistance values of the thermal model elements. Thermal resistance values for the thermal model elements are then determined based on the total thermal resistance value and the changed total thermal resistance values. The structure function is divided into portions associated with the thermal model elements based on the thermal resistance values for the thermal model elements.