Transaction correlation system

• US 9,208,271 B1
• Filed: 11/19/2010
• Issued: 12/08/2015
• Est. Priority Date: 11/19/2010
• Status: Expired due to Fees

• Current Assignee: Cadence Design Systems Incorporated (Cadence Group)
• Original Assignee: Cadence Design Systems Incorporated (Cadence Group)
• Inventors: Meir, Reshef, Hollander, Yoav, Givaty, Ohad, Kinderman, Yael
• Primary Examiner(s): Rivas, Omar Fernandez
• Assistant Examiner(s): Calle, Angel
• Application Number:
  US12/950,613
• Time in Patent Office: 1,845 Days
• Field of Search: 703/14
• US Class Current: 1/1
• CPC Class Codes: G06F 11/362 Software debugging
• CPC Class Codes: G06F 11/3692 for test results analysis
• CPC Class Codes: G06F 30/30 Circuit design
• CPC Class Codes: G06F 30/33 Design verification, e.g. functional simulation or model checking
• CPC Class Codes: G06F 30/3308 using simulation

Abstract

Embodiments provide methods, systems, and devices involving transaction correlation tools that may record a limited number of run attributes yet are likely to be important in the debugging process. Some embodiments may include novel tabular representations of the runs. Embodiments may allow the user to specify directives for the recording of the runs and the creation of these tables. Embodiments may include comparing sets of failing and passing runs, which may be generated at random. This approach is called statistical debugging, as it employs statistical tools to find attributes of the DVE that tend to co-occur with the failure.

Claims

1. A method of automated debugging of a design verification environment, the method comprising:

identifying a plurality of attributes of the design verification environment;

performing a plurality of simulation runs of the design verification environment;

recording a plurality of samples for each of the plurality of attributes from the plurality of simulation runs, wherein each sample includes a plurality of values of the plurality of attributes;

determining a subset of the simulation runs that fail;

determining a subset of simulation runs that pass;

identifying a subset of the plurality of attributes such that a distribution of values of the subset of attributes for the passing runs is different from a distribution of values of the subset of attributes for the failing runs;

generating a log of the plurality of simulation runs;

generating a tabular description based upon the log, wherein identifying the subset is based upon, at least in part, the tabular description;

utilizing a plurality of flattened tables as an input to a transaction correlation algorithm to determine one or more bugs in the design verification environment;

determining a measure for each passing run, wherein each measure for each passing run is based on a measure of the values sampled in the respective passing run;

determining a measure for each failing run, wherein each measure for each failing run is based on a measure of the values sampled in the respective failing run;

wherein the measure of the respective value sampled in the passing run is proportional to (A+C/D)/(B+1)−

(C−

C/D)/(D−

1) and the measure of the respective value sampled in the failing runs is proportional to (A+1)/(B+1)−

(C−

1)/(D−

1), wherein;

A=the number of failing runs with the respective value;

B=the number of failing runs;

C=the number of passing runs with the respective value; and

D=the number of passing runs.

2. The method of claim 1, wherein identifying the subset of the plurality of attributes further comprises:

determining an average of the measures of the passing runs;

determining an average of the measures of the failing runs; and

utilizing a difference between the average of the measures of the failing runs and the average of the passing runs to identify the subset of the plurality of attributes.

3. The method of claim 2, further comprising:

identifying one or more values from the identified subset of attributes, wherein the measure of the one or more respective identified values sampled in the respective failing run is greater than the average of the measures of the passing runs; and

presenting the one or more identified values to a user.

4. The method of claim 1, further comprising:

treating each passing run as if it were a failing run.

5. The method of claim 1, wherein an expectation value of the measure of a respective value in the failing run equals an expectation value of the measure of the respective value in the passing run when a value is generated at random.

6. The method of claim 1, further comprising creating a plurality of flattened tables based on the recorded plurality of samples for each simulation run and wherein identifying the subset of the plurality of attributes such that the distribution of values of the subset of attributes for the passing runs is different from the distribution of values of the subset of attributes for the failing runs utilizing the flattened tables.

7. The method of claim 1, further comprising receiving the plurality of identified attributes from a user.

8. The method of claim 1, wherein the design verification environment comprises a design under test and a verification environment.

9. A system for automated debugging of a design verification environment, the system comprising:

a storage medium;

a processor coupled with the storage medium, the processor configured for automated debugging of the design verification environment of electronic design automation by a configuration to;

identify a plurality of attributes of the design verification environment;

perform a plurality of simulation runs of the design verification environment;

record a plurality of samples for each of the plurality of attributes from the plurality of simulation runs, wherein each sample includes a plurality of values of the plurality of attributes;

determine a subset of the simulation runs that fail;

determine a subset of simulation runs that pass;

identify a subset of the plurality of attributes such that a distribution of values of the subset of attributes for the passing runs is different from a distribution of values of the subset of attributes for the failing runs;

generate a log of the plurality of simulation runs;

generate a tabular description based upon the log, wherein identifying the subset is based upon, at least in part, the tabular description; and

utilize a plurality of flattened tables as an input to a transaction correlation algorithm to determine one or more bugs in the design verification environment;

determine a measure for each passing run, wherein each measure for each passing run is based on a measure of the values sampled in the respective passing run;

determine a measure for each failing run, wherein each measure for each failing run is based on a measure of the values sampled in the respective failing run;

wherein the measure of the respective value sampled in the passing run is proportional to (A+C/D)/(B+1)−

(C−

C/D)/(D−

1) and the measure of the respective value sampled in the failing runs is proportional to (A+1)/(B+1)−

(C−

1)/(D−

1), wherein;

A=the number of failing runs with the respective value;

B=the number of failing runs;

C=the number of passing runs with the respective value; and

D=the number of passing runs.

10. The system for automated debugging of a design verification environment of claim 9, wherein identifying the subset of the plurality of attributes further comprises a configuration to:

determine an average of the measures of the passing runs;

determine an average of the measures of the failing runs; and

utilize a difference between the average of the measures of the failing runs and the average of the passing runs to identify the subset of the plurality of attributes.

11. The system for automated debugging of a design verification environment of claim 10, wherein the processor is further configured by a configuration to:

identify one or more values from the identified subset of attributes, wherein the measure of the one or more respective identified values sampled in the respective failing run is greater than the average of the measures of the passing runs; and

present the one or more identified values to a user.

12. The system for automated debugging of a design verification environment of claim 9, wherein the processor is further configured by a configuration to:

treat each passing run as if it were a failing run.

13. The system for automated debugging of a design verification environment of claim 9, wherein an expectation value of the measure of a respective value in the failing run equals an expectation value of the measure of the respective value in the passing run when a value is generated at random.

14. The system for automated debugging of a design verification environment of claim 9, wherein the processor is further configured by a configuration to:

create a plurality of flattened tables based on the recorded plurality of samples for each simulation run and wherein identifying the subset of the plurality of attributes such that the distribution of values of the subset of attributes for the passing runs is different from the distribution of values of the subset of attributes for the failing runs utilizing the flattened tables.

15. The system for automated debugging of a design verification environment of claim 9, wherein the processor is further configured by a configuration to:

receive the plurality of identified attributes from a user.

16. A non-transitory machine-readable storage medium containing program instructions that, when executed by a controller within a computer, cause the controller to execute a method of automated debugging of a design verification environment, the method comprising:

identifying a plurality of attributes of the design verification environment;

performing a plurality of simulation runs of the design verification environment;

recording a plurality of samples for each of the plurality of attributes from the

plurality of simulation runs, wherein each sample includes a plurality of values of the plurality of attributes;

determining a subset of the simulation runs that fail;

determining a subset of simulation runs that pass;

identifying a subset of the plurality of attributes such that a distribution of values of the subset of attributes for the passing runs is different from a distribution of values of the subset of attributes for the failing runs;

generating a log of the plurality of simulation runs;

generating a tabular description based upon the log, wherein identifying the subset is based upon, at least in part, the tabular description; and

utilizing a plurality of flattened tables as an input to a transaction correlation algorithm to determine one or more bugs in the design verification environment;

determining a measure for each passing run, wherein each measure for each passing run is based on a measure of the values sampled in the respective passing run;

determining a measure for each failing run, wherein each measure for each failing run is based on a measure of the values sampled in the respective failing run;

wherein the measure of the respective value sampled in the passing run is proportional to (A+C/D)/(B+1)−

(C−

C/D)/(D−

1) and the measure of the respective value sampled in the failing runs is proportional to (A+1)/(B+1)−

(C−

1)/(D−

1), wherein;

A=the number of failing runs with the respective value;

B=the number of failing runs;

C=the number of passing runs with the respective value; and

D=the number of passing runs.

17. The machine-readable storage medium of claim 16, wherein identifying the subset of the plurality of attributes further comprises:

determining an average of the measures of the passing runs;

determining an average of the measures of the failing runs; and

utilizing a difference between the average of the measures of the failing runs and the average of the passing runs to identify the subset of the plurality of attributes.

18. The machine-readable storage medium of claim 16, further comprising:

identifying one or more values from the identified subset of attributes, wherein the measure of the one or more respective identified values sampled in the respective failing run is greater than the average of the measures of the passing runs; and

presenting the one or more identified values to a user.

19. The machine-readable storage medium of claim 16, further comprising:

treating each passing run as if it were a failing run.

20. The machine-readable storage medium of claim 16, wherein an expectation value of the measure of a respective value in the failing run equals an expectation value of the measure of the respective value in the passing run when a value is generated at random.

21. The machine-readable storage medium of claim 16, further comprising creating a plurality of flattened tables based on the recorded plurality of samples for each simulation run and wherein identifying the subset of the plurality of attributes such that the distribution of values of the subset of attributes for the passing runs is different from the distribution of values of the subset of attributes for the failing runs utilizing the flattened tables.

22. The machine-readable storage medium of claim 16, further comprising receiving the plurality of identified attributes from a user.

23. A method of automated debugging in a design verification environment, the method comprising:

receiving a set of attributes of the design verification environment from a user;

performing a plurality of simulation runs of the design verification environment;

recording a plurality of samples for each of the plurality of user provided attributes from the plurality of simulation runs, wherein each sample includes a plurality of values of the plurality of attributes;

creating a plurality of flattened tables based on the recorded plurality of samples for each simulation run, wherein the plurality of samples are provided in a log of recorded data, the log of recorded data used to generate the plurality of flattened tables; and

utilizing the plurality of flattened tables as an input to a transaction correlation algorithm to determine one or more bugs in the design verification environment;

determining a measure for each passing run, wherein each measure for each passing run is based on a measure of the values sampled in the respective passing run;

determining a measure for each failing run, wherein each measure for each failing run is based on a measure of the values sampled in the respective failing run;

wherein the measure of the respective value sampled in the passing run is proportional to (A+C/D)/(B+1)−

(C−

C/D)/(D−

1) and the measure of the respective value sampled in the failing runs is proportional to (A+1)/(B+1)−

(C−

1)/(D−

1), wherein;

A=the number of failing runs with the respective value;

B=the number of failing runs;

C=the number of passing runs with the respective value; and

D=the number of passing runs.

24. The method of claim 23, wherein the sets of attributes are related.

25. The method of claim 24, wherein the sets of attributes are associated with a packet or a transaction.

26. The method of claim 24, wherein the sets of attributes comprise at least a part of a coverage definition.

27. The method of claim 23, further comprising joining two or more of the plurality of flattened tables.

28. A non-transitory machine-readable storage medium containing program instructions that, when executed by a controller within a computer, cause the controller to execute a method of automated debugging of a design verification environment, the method comprising:

receiving a set of attributes of the design verification environment from a user;

performing a plurality of simulation runs of the design verification environment;

recording a plurality of samples for each of the plurality of user provided attributes from the plurality of simulation runs, wherein each sample includes a plurality of values of the plurality of attributes;

creating a plurality of flattened tables based on the recorded plurality of samples for each simulation run, wherein the plurality of samples are provided in a log of recorded data, the log of recorded data used to generate the plurality of flattened tables; and

utilizing the plurality of flattened tables as an input to a transaction correlation algorithm to determine one or more bugs in the design verification environment;

determining a measure for each passing run, wherein each measure for each passing run is based on a measure of the values sampled in the respective passing run;

determining a measure for each failing run, wherein each measure for each failing run is based on a measure of the values sampled in the respective failing run;

wherein the measure of the respective value sampled in the passing run is proportional to (A+C/D)/(B+1)−

(C−

C/D)/(D−

1) and the measure of the respective value sampled in the failing runs is proportional to (A+1)/(B+1)−

(C−

1)/(D−

1), wherein;

A=the number of failing runs with the respective value;

B=the number of failing runs;

C=the number of passing runs with the respective value; and

D=the number of passing runs.

29. The machine-readable storage medium of claim 28, wherein the sets of attributes are related.

30. The machine-readable storage medium of claim 29, wherein the sets of attributes are associated with a packet or a transaction.

31. The machine-readable storage medium of claim 29, wherein the sets of attributes comprise at least a part of a coverage definition.

32. The machine-readable storage medium of claim 28, further comprising joining two or more of the plurality of flattened tables.