Synopsys, Inc.

Bhaskar Pal

Rajarshi Mukherjee

Sauresh Bhowmick

Sanjay Gulati

Kaushik De

Sourasis Das

Esha Dutta

Eduard Rudolf Cerny

David L Allen

Parijat Biswas

Pallab Dasgupta

Pravash Chandra Dash

Partha Pratim Chakrabarti

Danish Jawed

Nishant Patel

Sharad Gaur

Malitha Kulatunga

Aditya Daga

Sachin Bansal

Harsha Vardhan

Gaurav Pratap

The independent claims of this patent signify a concise description of embodiments. An automatic process for determining and/or predicting the original root-cause(s) of a violation is proposed using two major enhancements on top of the current VC-Static solution. First, an information repository is created by mining various Static checker components' analysis information, and second, an analysis framework is created which systematically prunes the above-mentioned information repository to find the actual root cause(s) of the violation. This Abstract is not intended to limit the scope of the claims.

Automatic root cause analysis of complex static violations by static information repository exploration

Disclosed herein are system, method, and computer-readable storage device embodiments for implementing automated root-cause analysis for static verification. An embodiment includes a system with memory and processor(s) configured to receive a report comprising violations and debug fields, and accept a selection of a seed debug field from among the plurality of debug fields. Clone violations may be generated by calculating an overlay of a given violation of the violations and a seed debug field, yielding possible values for a subset of debug fields. A clone violation may be created for a combination of the at least two second debug fields, populating a projection matrix, which may be used to map violations and clone violations to corresponding numerical values in the projection matrix and determine a violation cluster based on the mapping having corresponding numerical values and score(s) satisfying a threshold, via ML. Clustering may further be used to generate visualizations.

Automated root-cause analysis, visualization, and debugging of static verification results

State table complexity reduction in a hierarchical verification flow is provided by identifying peripheral supplies and non-peripheral supplies in a hierarchical group in a hierarchical logical block model of a circuit based on whether logic blocks associated with the power supplies provide outputs to or receive inputs from circuity external to the hierarchical group; merging associated power state tables for the peripheral supplies and the non-peripheral supplies in the hierarchical group to create a merged power state table for the hierarchical group; removing, by a processing device, any power states associated with the non-peripheral supplies from the merged power state table to create a reduced power state table; and modeling a reduced logical block based on the reduced power state table.

State table complexity reduction in a hierarchical verification flow

A system and method generates cluster-based power architecture interfaces for an integrated circuit (IC) design under test (DUT) debugging by receiving design data for an IC DUT, determining power characteristic data for the IC DUT, generating display components within a graphical user interface (GUI) corresponding to individual components encompassed within a power intent hierarchy corresponding with the IC DUT, generating graphical links between displayed components, overlaying interactive elements corresponding with generated violation clusters over graphical links, and providing root-cause interactive elements within the generated GUI having visual associations with the interactive components corresponding with particular violation clusters.

System and method for generating a cluster-based power architecture user interface

A data analysis engine is implemented in a testbench to improve coverage convergence during simulation of a device-under-validation (DUV). During a first simulation phase initial stimulus data is generated according to initial random variables based on user-provided constraint parameters. The data analysis engine then uses a time-based technique to match coverage variables sampled from simulation response data with corresponding initial random variables, determines a functional dependency (relationship) between the sampled coverage variables and corresponding initial random variables, then automatically generates revised constraint parameters based on the functional dependency. The revised constraint parameters are then used during a second simulation phase to generate focused random variables used to stimulate the DUV to reach additional coverage variables. In one embodiment, the functional dependency is determined by cross-correlating sampled coverage variables and corresponding initial random variables.

Automated coverage convergence by correlating random variables with coverage variables sampled from simulation result data

One embodiment of the present invention provides systems and techniques to extract assume properties from a constrained random test-bench. During operation, the system can receive a constrained random test-bench for verifying the design-under-test (DUT), wherein the constrained random test-bench includes a statement which assigns a random value to a random variable according to a constraint. Next, the system can modify the constrained random test-bench by replacing the statement with another statement which assigns a free input variable's value to the random variable. The system can also add a statement to the constrained random test-bench that toggles a marker variable to localize the scope of the statement. The system can then generate an assume property which models the constraint on the free input variable. The assume property can then be used by a formal property verification tool to verify the DUT.

Method and apparatus for extracting assume properties from a constrained random test-bench

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Bengaluru, India

Bhaskar Pal