A method for managing transactions burstiness associated with a sequence of transactions generated in a test environment for verifying a Device Under Test (DUT) is disclosed. In some embodiments, the method includes processing a plurality of signals associated with a sequence of transactions. The method further includes generating a transactions burstiness signature representative of the sequence of transactions based on processing a set of signals from the plurality of signals. The method further includes analysing the transactions burstiness signature to identify at least one pattern of interest. The method further includes iteratively providing an input comprising at least one missing pattern of interest. The method further includes iteratively generating a subsequent sequence of transactions and a subsequent transactions burstiness signature associated with the subsequent sequence of transactions.

An automatic robot control system and methods relating thereto are described. These systems include components such as a touch screen panel (“TSP”) robot controller for controlling a TSP robot, a camera robot controller for controlling a camera robot and an audio robot controller for controlling an audio robot. The TSP robot operates inside a TSP testing subsystem, the camera robot operates inside a camera testing subsystem, and the audio robot operates inside an audio testing subsystem. Inside the audio testing subsystem, an audio signals measurement system, using a bi-directional coupling, controls the operation of the audio robot controller. In this control scheme, a test application controller is designed to control the different types of subsystem robots. Methods relating to TSP, camera, and audio robots, and their controllers, taken individually or in combination, for automatic testing of device functionalities are also described.

In general, a device comprising a processor and a memory may be configured to perform various aspects of the techniques described in this disclosure. The processor may conduct, based on configuration parameters, each of a plurality of simulation iterations within the test environment to collect a corresponding plurality of simulation datasets representative of operating states of the network device. The processor may perform a regression analysis with respect to each of the plurality of configuration parameters and each of the plurality of simulation datasets to generate a light weight model representative of the network device that predicts an operating state of the network device. The processor may output the light weight model for use in a computing resource restricted network device to enable prediction of the operating state of the computing resource restricted network device when configured with the configuration parameters. The memory may store the light weight model.

An automatic robot control system and methods relating thereto are described. These systems include components such as a touch screen panel (“TSP”) robot controller for controlling a TSP robot, a camera robot controller for controlling a camera robot and an audio robot controller for controlling an audio robot. The TSP robot operates inside a TSP testing subsystem, the camera robot operates inside a camera testing subsystem, and the audio robot operates inside an audio testing subsystem. Inside the audio testing subsystem, an audio signals measurement system, using a bi-directional coupling, controls the operation of the audio robot controller. In this control scheme, a test application controller is designed to control the different types of subsystem robots. Methods relating to TSP, camera, and audio robots, and their controllers, taken individually or in combination, for automatic testing of device functionalities are also described.

A power supply health check system for checking a health state of an under-test power supply is provided. The under-test power supply supplies power to a main board which has a voltage signal during operation. The health check system includes a detecting module, a deep learning model, and a processing unit. The detecting module is electrically connected to the main board to detect the voltage signal and convert the voltage signal into a digital signal. The deep learning model is established by using frequency-domain voltage data of a plurality of healthy power. The processing unit is configured to: collect the digital signal and store the digital signal as under-test time-domain voltage data; convert the under-test time-domain voltage data into under-test frequency-domain voltage data; and calculate, based on the under-test frequency-domain voltage data and the deep learning model, a health indicator for determining the health state of the under-test power supply.

Disclosed are techniques for chip-to-chip (C2C) serial communications, such as communications between chiplets on a multi-chip package. In some aspects, a method of on-die monitoring of C2C links comprises detecting a change of the C2C link from a first link state to a second link state and storing link state change information in an on-die first-in, first-out (FIFO) buffer. The link state change information indicates the first link state, the duration of time the C2C link was in the first link state, and the speed of the C2C link in the first link state. Upon detecting a request for link state change information, link state change information is retrieved from the FIFO buffer and transmitted serially to an output pin of the die, such as a general purpose input/output (GPIO) pin.

Methods and computing devices for allocating test pods to a distributed computing system for executing a test plan on a device-under-test (DUT). Each test pod may include a test microservice including one or more test steps and an event microservice specifying function relations between the test microservice and other test microservices. The test pods are allocated to different servers to perform a distributed execution of the test plan on the DUT through one or more test interfaces.

An automatic robot control system and methods relating thereto are described. These systems include components such as a touch screen panel (“TSP”) robot controller for controlling a TSP robot, a camera robot controller for controlling a camera robot and an audio robot controller for controlling an audio robot. The TSP robot operates inside a TSP testing subsystem, the camera robot operates inside a camera testing subsystem, and the audio robot operates inside an audio testing subsystem. Inside the audio testing subsystem, an audio signals measurement system, using a bi-directional coupling, controls the operation of the audio robot controller. In this control scheme, a test application controller is designed to control the different types of subsystem robots. Methods relating to TSP, camera, and audio robots, and their controllers, taken individually or in combination, for automatic testing of device functionalities are also described.

A configuration generating method for devices is applied to connecting ports and external devices connected to the connecting ports. The method includes the following steps: determining communication protocol types of the connecting ports respectively; generating a sequence list according to a plurality of device data, wherein each of the device data is corresponding to a communication protocol, the device data with ccTalk protocol are categorized in a first priority group, the device data with MDB protocol are categorized in a third sequence group, the device data other than those of the first priority group and the third priority group are categorized in a second priority group; and, testing the external devices sequentially and generating communication results according to the sequence list and the device data corresponding to the communication protocol types, and then generating a connecting ports configuration data of connecting ports according to the communication results.

There are disclosed various methods, apparatuses and computer program products for a testing apparatus. In accordance with an embodiment the testing apparatus comprises a frame; a gripping head for gripping a device to be tested; a first movement element for moving the gripping head with respect to the frame; a movement detector to detect at least one of a location and a position of the device; a touching element for touching the device; an imaging device for capturing images of the device; a display for generating visual information for capturing by the device; a set of sensors for examining operations of the device; a set of actuators for providing signals for reception by the device; and a set of plugs adapted to be inserted into a socket of the device.