Exemplary embodiments provide computer-implemented methods, mediums, and apparatuses configured to provide an interactive analytical method debugger for an analytical laboratory system. The analytical laboratory system may include a laboratory analytical device with a number of settings, parameters, etc. The laboratory analytical device may process a sample according to an analytical method that (among other things) defines a configuration for the device. The settings for the method may be organized into categories. The interactive debugger identifies problems with the method (e.g., incompatibilities, values out of range, etc.) and automatically allow the user to view the category of the method that is relevant to addressing the issue. Possible solutions may be proposed in the debugger interface, allowing the user to quickly identify and address the problem. Embodiments are particularly well-suited to situations where a method is ported from an old device to a new device.

A system, method, and memory for handling real-time transactional events is disclosed. The exemplary system a processor to detect and add an event to a queue and identify an associated event type. Event types can require downstream processing by at least one provider. The processor decomposes the event into tasks by comparison to event types which associate downstream provider requirements to tasks and routes. One or more routes are assigned to the tasks, each route defined by at least one processor of a plurality of processors. One or more routes are defined by transmitting a request for downstream processing to the at least one provider. The processor, upon detecting incomplete performance of the one or more routes, either updates the tasks associated with the incomplete route, or marks the event associated with the route as incomplete in the queue.

The present invention relates to computerized (“smart”) mobile electronic devices and more particularly, to a system and methods of diagnosing and repairing malfunctions in smart mobile electronic devices, including a diagnostic process that utilizes decisions based on Big Data that holds information of multiple devices and offers a “disable components” (i.e., turn-off components) solution in order to overcome the problem without flashing a firmware or doing a factory-reset.

Some embodiments may facilitate software development and operations for an enterprise. A communication input port may receive information associated with a software continuous integration/deployment pipeline of the enterprise. An intelligent software agent platform, coupled to the communication input port, may listen for a trigger indication from the software continuous integration/deployment pipeline. Responsive to the trigger indication, the intelligent software agent platform may apply system configuration information and rule layer information to extract software log data and apply a machine learning model to the extracted software log data to generate a pipeline health check analysis report. The pipeline health check analysis report may include, for example, an automatically generated prediction associated with future operation of the software continuous integration/deployment pipeline. The intelligent software agent platform may then facilitate transmission of the pipeline health check analysis report via a communication output port and a distributed communication network.

In a method of managing a debugging log in a storage device, an event trigger signal is generated based on an external power supply voltage and a plurality of configuration control signals. The event trigger signal is activated in response to an event of interest being issued for generating and storing the debugging log. The debugging log represents information associated with errors occurring in the storage device. The debugging log is generated based on the event trigger signal. The debugging log is stored in a nonvolatile memory. The event of interest includes at least one of a power up event a reset event, a link up event, a link down event or a power down event.

An improved SDK includes a set of APIs and a crash handler registered with the operating system. Each API is an interface accessible by a computer software application. Up on entrance, each API determines the current thread identifier, and inserts it into a list if it is not already in the list. Each thread identifier corresponds to an API call counter, which is incremented by one at the entrance and decremented by one at the exit point of the API. The SDK also records the identifier of the thread it creates for callback functions. When a crash occurs, the crash handler is executed. It determines that the crash is related to a callback interface if the crash thread identifier matches the callback thread identifier. The crash is determined to be caused by the SDK if the API call counter corresponding to the crash thread identifier is greater than zero.

Intelligent collection and analysis of in-app failure data is disclosed herein. Upon an application failure in a client device, the client device may collect failure information uniquely identifying a specific failure and provide the failure information to an analysis system. The analysis system may identify a specific failure that identifies the application and a specific portion of the code in the application, based on the failure information and match an action correlated to the specific failure where the action is uniquely designed to resolve the specific failure in the application. The action may include instructions for the client device used to intelligently lead to a resolution of the specific failure. The analysis system may transmit the action to the client device to perform the action and provide any follow up information to the analysis server. The analysis server may use the information to further analyze the specific failure.

Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for data processing. The method described herein includes determining identification information for an operation, wherein the identification information includes at least one field indicating content of the operation and a field indicating a unique identification of the operation. The method further includes identifying, based on the identification information, log entries for the operation in log files for at least one microservice invoked by the operation. The method further includes determining a log for the operation, wherein the log includes the identified log entries. With the solution for data processing of the present application, it is possible to easily acquire logs for an operation using identification information that includes a field indicating the content of the operation, so as to facilitate targeted analysis of the operation based on the content of the operation.

A data selection device assists selection of suitable training data used for sign detection, and includes: a storage unit configured to store time-series sensor data acquired from a sensor with respect to a failure prediction target device; a data classification unit configured to classify the time-series sensor data into a first data set and a second data set while allowing the first data set and the second data set to overlap each other; a training data selection unit configured to select a subset of the second data set based on a value range of the first data set; a training data evaluation unit configured to calculate an evaluation index indicating a suitability of a failure prediction model as training data based on the selected subset; and a data selection condition search unit configured to search for the value range of the first data set that maximizes the evaluation index.

Aspects of the present disclosure describe improved supercontinuum generation based upon alternating optical dispersion along a waveguide length that advantageously generates much more spectral bandwidth than possible with conventional, prior art techniques without losing coherence as well as supporting a larger range of pulse energies (i.e., for lower than conventionally allowed pulse energies or high pulse energies).