A computer-implemented method is provided for redundancy reduction for driving test scenarios. The method includes receiving an original test set of driving scenarios and a driving model which simulates a vehicle behavior under a driving scenario inputted to the driving model. The method includes, for each driving scenario of the original test set, obtaining vehicle dynamics timeseries data as an output of the driving model. The method includes determining similar driving scenarios by comparing driving model outputs. The method additionally includes creating a new test set of driving scenarios by discarding duplicated ones of the similar driving scenarios from the original test set.

A computer-implemented method is provided for redundancy reduction for driving test scenarios. The method includes receiving an original test set of driving scenarios and a driving model which simulates a vehicle behavior under a driving scenario inputted to the driving model. The method includes, for each driving scenario of the original test set, obtaining vehicle dynamics timeseries data as an output of the driving model. The method includes determining similar driving scenarios by comparing driving model outputs. The method additionally includes creating a new test set of driving scenarios by discarding duplicated ones of the similar driving scenarios from the original test set.

A system, method, and computer program are provided for combining results of event processing received from a plurality of virtual processes or servers. In use, an event is sent to a plurality of virtual processes or virtual servers. Further, a result of processing of the event is received from each of the virtual processes or virtual servers. In addition, the results received from the plurality of virtual processes or virtual servers are combined.

A system, method, and computer program are provided for combining results of event processing received from a plurality of virtual processes or servers. In use, an event is sent to a plurality of virtual processes or virtual servers. Further, a result of processing of the event is received from each of the virtual processes or virtual servers. In addition, the results received from the plurality of virtual processes or virtual servers are combined.

Aspects of the present disclosure provide a processor having: an execution unit configured to execute machine code instructions, at least one of the machine code instructions requiring multiple cycles for its execution; instruction memory holding instructions for execution, wherein the execution unit is configured to access the memory to fetch instructions for execution; an instruction injection mechanism configured to inject an instruction into the execution pipeline during execution of the at least one machine code instruction fetched from the memory; the execution unit configured to pause execution of the at least one machine code instruction, to execute the injected instruction to termination, to detect termination of the injected instruction and to automatically recommence execution of the at least one machine code instruction on detection of termination of the injected instruction.

Aspects of the present disclosure provide a processor having: an execution unit configured to execute machine code instructions, at least one of the machine code instructions requiring multiple cycles for its execution; instruction memory holding instructions for execution, wherein the execution unit is configured to access the memory to fetch instructions for execution; an instruction injection mechanism configured to inject an instruction into the execution pipeline during execution of the at least one machine code instruction fetched from the memory; the execution unit configured to pause execution of the at least one machine code instruction, to execute the injected instruction to termination, to detect termination of the injected instruction and to automatically recommence execution of the at least one machine code instruction on detection of termination of the injected instruction.

A failure analysis system identifies a root cause of a failure (or other health issue) in a virtualized computing environment and provides a recommendation for remediation. The failure analysis system uses a model-based reasoning (MBR) approach that involves building a model describing the relationships/dependencies of elements in the various layers of the virtualized computing environment, and the model is used by an inference engine to generate facts and rules for reasoning to identify an element in the virtualized computing environment that is causing the failure. Then, then the failure analysis system uses a decision tree analysis (DTA) approach to perform a deep diagnosis of the element, by traversing a decision tree that was generated by combining the rules for reasoning provided by the MBR approach, in conjunction with examining data collected by health monitors. The result of the DTA approach is then used to generate the recommendation for remediation.

A failure analysis system identifies a root cause of a failure (or other health issue) in a virtualized computing environment and provides a recommendation for remediation. The failure analysis system uses a model-based reasoning (MBR) approach that involves building a model describing the relationships/dependencies of elements in the various layers of the virtualized computing environment, and the model is used by an inference engine to generate facts and rules for reasoning to identify an element in the virtualized computing environment that is causing the failure. Then, then the failure analysis system uses a decision tree analysis (DTA) approach to perform a deep diagnosis of the element, by traversing a decision tree that was generated by combining the rules for reasoning provided by the MBR approach, in conjunction with examining data collected by health monitors. The result of the DTA approach is then used to generate the recommendation for remediation.

Techniques for automatically selecting device tests for testing devices configured for operation in wireless communication networks, based upon maintenance releases (MRs) received from original equipment manufacturers. When an MR with changes for a device is received, the MR may be analyzed in order to determine what the changes pertain to with respect to the device. The changes may be clustered with respect to requirements for the changes and a knowledge base may be consulted by a recommendation engine in order to determine candidate tests for testing the MR. The candidate tests may be based upon previous tests, failed tests and, relevant tests. Based at least in part on the identified previous tests, failed tests and relevant tests, one or more tests may be selected for testing devices with respect to the newly received MR.

Techniques for automatically selecting device tests for testing devices configured for operation in wireless communication networks, based upon maintenance releases (MRs) received from original equipment manufacturers. When an MR with changes for a device is received, the MR may be analyzed in order to determine what the changes pertain to with respect to the device. The changes may be clustered with respect to requirements for the changes and a knowledge base may be consulted by a recommendation engine in order to determine candidate tests for testing the MR. The candidate tests may be based upon previous tests, failed tests and, relevant tests. Based at least in part on the identified previous tests, failed tests and relevant tests, one or more tests may be selected for testing devices with respect to the newly received MR.