The present disclosure relates to a verification apparatus for a vehicle-mounted control apparatus having a first program processing unit that executes a current program, based on an output of a sensor and outputs a processing result to an actuator unit. Because the verification apparatus has a second program processing unit that executes the current program and outputs a processing result, a third program processing unit that shares the output of the sensor unit with the second program processing unit and that executes a new program and outputs a processing result, and a comparison determination unit that compares the respective outputs, it is made possible to perform a regression test effective for the new program at low cost, without affecting operation of the vehicle-mounted control apparatus.

A test support apparatus (100) includes an operation definition information conversion unit (120). Regarding each device included in a test subject that includes at least one device, the operation definition information conversion unit (120) generates for each state of each device, state transition information indicating a transition of operation to be executed by each device included in the test subject, based on operation definition information indicating the operation to be executed by each device and an occurrence condition and a release condition corresponding to the operation to be executed by each device.

An anomaly detection processing method and device for solid-state drive (SSD) are provided. The anomaly detection processing method for SSD including collecting test data of an SSD, the test data including at least one of self-monitoring, analysis and reporting technology S.M.A.R.T. data, NAND flash cell threshold voltage distribution data, and bit error rate eye diagram data, determining whether the SSD has an anomaly based on the test data, and determining an anomaly cause of the SSD based on a subset of test data, the subset including specific test data based on which the SSD has been determined to have an anomaly may be provided.

A method, system, and computer program product for performing user-initiated logging and auto-correction in hardware/software systems. Embodiments commence upon identifying a set of test points and respective instrumentation components, then determining logging capabilities of the instrumentation components. The nature and extent of the capabilities and configuration of the components aid in generating labels to describe the various logging capabilities. The labels are then used in a user interface so as to obtain user-configurable settings which are also used in determining auto-correction actions. A measurement taken at a testpoint may result in detection of an occurrence of a certain condition, and auto-correction steps can be taken by retrieving a rulebase comprising a set of conditions corresponding to one or more measurements, and corrective actions corresponding to the one or more conditions. Detection of a condition can automatically invoke any number of processes to apply a corrective action and/or emit a recommendation.

Methods and arrangements for identifying root causes of system failures in a distributed system said method including: utilizing at least one processor to execute computer code that performs the steps of: recording, in a storage device, collected machine state data, wherein the collected machine state data are added to historical machine state data; creating, based on the historical machine state data, a healthy map model; detecting at least one failed machine state in the distributed system; comparing the failed machine state against the healthy map model; identifying, based on the comparison, at least one root cause of the failed machine state; and displaying, on a display device, a ranked list comprising the at least one root cause. Other variants and embodiments are broadly contemplated herein.

Generation of a performance determination report for an Extract, Transform, Load (ETL) job includes decomposing the ETL job into two or more stage instances, and identifying one or more conditions for each of the stage instances. A set of tests for each of the identified conditions are generated. A first set of test results are generated by performing the set of tests. It is determined whether a test result from the first set of test results is outside of a first range. Conditions that can be identified include a non-volatile free memory condition, a network reliability condition, a network configuration condition, an application availability condition, a database availability condition, a database performance condition, a schema validity condition, an installed libraries condition, a configuration parameter condition, a volatile free memory condition, and a third party tool condition.

A test unit, operating in a first hardware operating state, receives a request for the input data from a test platform. In response to the receiving the request, the test unit determines that retrieving the input data requires the test unit to be in a second hardware operating state. In response to the determining, the test unit transitions from the first hardware operating state to the second operating hardware state. In the second hardware operating state, the test unit retrieves the input data. Once the test unit transitions to the second and correct hardware operating state, the test unit transmits the input data to the test platform.

A method may include, in a computing device comprising at least one processor and a memory, generating at least one information beacon from each of a plurality of applications installed on the computing device. Each information beacon may include application analytics data associated with a corresponding application while the corresponding application is running on the computing device. The at least one information beacon from each of the plurality of applications may be stored in a common location in the computing device. The stored at least one information beacon may be dispatched from each of the plurality of applications to a network device communicatively coupled to the computing device. The generating may be triggered by beacon generation code implemented in each of the plurality of applications installed on the computing device.

Systems and techniques for identifying failure mechanisms based on a population of scan diagnostic reports is described. Given a population of scan diagnostic reports, a mixed membership model can be used for computing a topic distribution for each portion of each scan diagnostic report and a feature distribution for each topic. The failure mechanisms can be identified based on the topic distributions for the portions of the scan diagnostic reports and the feature distributions for the topics.

A test unit, operating in a first hardware operating state, receives a request for the input data from a test platform. In response to the receiving the request, the test unit determines that retrieving the input data requires the test unit to be in a second hardware operating state. In response to the determining, the test unit transitions from the first hardware operating state to the second operating hardware state. In the second hardware operating state, the test unit retrieves the input data. Once the test unit transitions to the second and correct hardware operating state, the test unit transmits the input data to the test platform.