An arrangement for automated testing of mobile devices comprising a learning arrangement for learning how to use test devices that do not match with an earlier already defined test case pattern. In the arrangement the learning arrangement generates instructions for performing a set of tasks. The tasks are then executed in the mobile device being tested. The mobile device provides feedback in form of error/success messages, screenshots, source code, return values and similar. Based on the feedback and earlier accumulated information the learning entity can generate a new set of instructions in order to execute the set of tasks successfully.

An arrangement for automated testing of mobile devices comprising a learning arrangement for learning how to use test devices that do not match with an earlier already defined test case pattern. In the arrangement the learning arrangement generates instructions for performing a set of tasks. The tasks are then executed in the mobile device being tested. The mobile device provides feedback in form of error/success messages, screenshots, source code, return values and similar. Based on the feedback and earlier accumulated information the learning entity can generate a new set of instructions in order to execute the set of tasks successfully.

A system and method of detecting defects in an analog circuit is provided. A method includes identifying a channel connected block (CCB) from a netlist, creating defect for the CCB to be injected during a simulation, obtaining a first measurement of an output node of the CCB by performing a first analog circuit simulation for the CCB based on providing excitations as inputs to the CCB and obtaining a second measurement of the output node of the CCB by performing a second analog circuit simulation for the CCB based on providing the excitations as the inputs to the CCB and injecting the defect. The method can further include determining a defect type based on the first measurement and the second measurement.

A system and method of detecting defects in an analog circuit is provided. A method includes identifying a channel connected block (CCB) from a netlist, creating defect for the CCB to be injected during a simulation, obtaining a first measurement of an output node of the CCB by performing a first analog circuit simulation for the CCB based on providing excitations as inputs to the CCB and obtaining a second measurement of the output node of the CCB by performing a second analog circuit simulation for the CCB based on providing the excitations as the inputs to the CCB and injecting the defect. The method can further include determining a defect type based on the first measurement and the second measurement.

An operation verifying apparatus of a first embodiment acquires a log indicating the content of a sequence of operations performed on a predetermined device, identifies corresponding functions from the log, and automatically generates a program based on the identified functions. Input data, which is to serve as an argument of each of these functions, is set. Execution sets as well as test scenarios are each structured by combining a program and input data. Then each execution set is continuously executed. As a result, an operation test using a test program is executed.

An operation verifying apparatus of a first embodiment acquires a log indicating the content of a sequence of operations performed on a predetermined device, identifies corresponding functions from the log, and automatically generates a program based on the identified functions. Input data, which is to serve as an argument of each of these functions, is set. Execution sets as well as test scenarios are each structured by combining a program and input data. Then each execution set is continuously executed. As a result, an operation test using a test program is executed.

One embodiment provides a method, including: receiving a dataset and a model corresponding to a bias checker, wherein the bias checker detects bias within both the dataset and the model, based upon a bias checking algorithm and a bias checking policy, wherein the dataset comprises a plurality of attributes; testing the bias checking algorithm of the bias checker by (i) generating test cases that modify the dataset by introducing bias therein and (ii) running the bias checker against the modified dataset; testing the bias checking policy of the bias checker by generating a plurality of test cases and running the bias checker against the plurality of test cases; and providing a notification to a user regarding whether the bias checker failed to indicate bias for one or more of the plurality of attributes.

One embodiment provides a method, including: receiving a dataset and a model corresponding to a bias checker, wherein the bias checker detects bias within both the dataset and the model, based upon a bias checking algorithm and a bias checking policy, wherein the dataset comprises a plurality of attributes; testing the bias checking algorithm of the bias checker by (i) generating test cases that modify the dataset by introducing bias therein and (ii) running the bias checker against the modified dataset; testing the bias checking policy of the bias checker by generating a plurality of test cases and running the bias checker against the plurality of test cases; and providing a notification to a user regarding whether the bias checker failed to indicate bias for one or more of the plurality of attributes.

Methods, systems, and computer readable media for smart network interface card testing are disclosed. One example method occurs at a network interface card (NIC) comprising a network processing unit executing a monitoring agent for monitoring data traversing the NIC. The method includes obtaining, from a test system or a test traffic generator, at least one test packet; generating, using the monitoring agent, NIC processing information associated with processing the at least one test packet, wherein generating the NIC processing information includes monitoring application layer events, presentation layer events, session layer events, transport layer events, network layer events, driver layer events, kernel layer events, or other events involving the NIC and generating the NIC processing information using the monitored events; and storing or providing the NIC processing information for data analysis.

Methods, systems, and computer readable media for smart network interface card testing are disclosed. One example method occurs at a network interface card (NIC) comprising a network processing unit executing a monitoring agent for monitoring data traversing the NIC. The method includes obtaining, from a test system or a test traffic generator, at least one test packet; generating, using the monitoring agent, NIC processing information associated with processing the at least one test packet, wherein generating the NIC processing information includes monitoring application layer events, presentation layer events, session layer events, transport layer events, network layer events, driver layer events, kernel layer events, or other events involving the NIC and generating the NIC processing information using the monitored events; and storing or providing the NIC processing information for data analysis.