In some examples, a prototype model that includes a representative subset of data points (e.g., inputs and output classifications) of a machine learning model is analyzed to efficiently interpret the machine learning model's behavior. Performance metrics such as a critic fraction, local explanation scores, and global explanation scores are determined. A local explanation score capture an importance of a feature of a test point to the machine learning model determining a particular class for the test point and is computed by comparing a value of a feature of a test point to values for prototypes of the prototype model. Using a similar approach, global explanation scores may be computed for features by combining local explanation scores for data points. A critic fraction may be computed to quantify a misclassification rate of the prototype model, indicating the interpretability of the model.

Provided is a service graph generation apparatus 10 for generating a service graph expressing a dependency relationship between components constituting a monitoring target service 50. The service graph generation apparatus 10 includes an acquisition unit 11 that acquires trace data including spans recording a parent-child relationship and time data of processing of components in a series of processing in a service, an analysis unit 13 that compares, for every piece of the trace data, time data between spans of the components having the same parent to estimate an order relationship or an exclusive relationship between the components, and a creation unit 14 that creates a service graph expressing all components formed of the monitoring target service 50, and the parent-child relationship, the order relationship, and the exclusive relationship between the components.

A storage device and an operating method thereof are provided. The storage device includes a memory configured to store parameter data used as an input in a neural network. The storage device also includes a storage controller configured to receive a request signal from a host. The storage controller is also configured to encode, based on the parameter data, log data in the neural network, the log data indicating contexts of the plurality of components, and transmit the encoded log data to the host.

Provided are a computer program product, system, and method for scanning a computing system to determine a computing system profile and problems to recommend actions to initiate with the computing system. A package is transmitted to the computing system including package code to scan the computing system to determine a computing system profile comprising a computing architecture and installed applications at the computing system. The computing system profile is processed to determine a recommended action to perform with respect to the computing system to improve operations of the computing system based on the computing system profile. A display element is generated in a user interface with information on the recommended action to enable a user of the computing system to implement the recommended action. The package code executes within the computing system without communicating over the network to an external system outside of a computing environment of the computing system.

A system for facilitating analysis of a software product is provided. The system includes processing circuitry that collects data logs from various technologies associated with at least one stage of a software development life cycle (SDLC) of the software product. The processing circuitry identifies entities associated with each collected data log, and standardizes the collected data logs such that each collected data log is standardized based on standard data formats associated with the identified entities. Each entity corresponds to at least one stage of the SDLC of the software product. Further, the processing circuitry updates data models associated with the entities based on the standardized data logs and generates a unified data model that is indicative of a correlation between the entities. Based on the correlation indicated by the unified data model, the processing circuitry executes an automated action.

Provided are a computer program product, system, and method for scanning a computing system to determine a computing system profile and problems to recommend actions to initiate with the computing system. A package is transmitted to the computing system including package code to scan the computing system to determine a computing system profile comprising a computing architecture and installed applications at the computing system. The computing system profile is processed to determine a recommended action to perform with respect to the computing system to improve operations of the computing system based on the computing system profile. A display element is generated in a user interface with information on the recommended action to enable a user of the computing system to implement the recommended action. The package code executes within the computing system without communicating over the network to an external system outside of a computing environment of the computing system.

A processing device and method for generating data reports from a data stream are provided. The processing device may include an analyzer that may identify a data record by detecting a start record event indicator and an end record event indicator within the data stream, the start and end record event indicators representing a start and an end of the respective data record, an extractor that may extract data of the identified data record from the data stream based on the start record event indicator and the end record event indicator, and a generator configured to generate, based on the event indicator, one or more events, wherein an event handler handles the one or more events to process the data record for inclusion into the data report.

A system with an interactive user interface for users to view and interact with sanitized log data received from a plurality of hosts, such as those associated with various services of an organization. The system may receive from hosts log files and/or metadata that have been filtered by agents executing on the respective hosts to remove or anonymize any sensitive or confidential information prior to transmission to the system. In some embodiments the system does further filtering of the sanitized data. Received sanitized data is parsed, indexed, and/or otherwise processed for optimal searching, and stored in a log pipeline. The system causes display of an electronic visualization interface.

A method for debugging a program, based on simulating an object program and comparing simulated waveforms with standard waveforms are applied in an electronic device. A simulated environment corresponding to the object program is established and multiple instructions from code of the object program are mapped against the standard waveforms. Trigger points are set in the object program, the object program is run from the trigger point and simulation waveforms are stored. The simulation waveforms are compared with the standard waveforms, and the location of a bug of the object program is found according a comparison. The bug may be resolved or cured. The electronic device utilizing the method is also disclosed.

A system and method for the analysis of log data is presented. The system uses SuperMinHash based locality sensitive hash signatures to describe the similarity between log lines. Signatures are created for incoming log lines and stored in signature indexes. Later similarity queries use those indexes to improve the query performance. The SuperMinHash algorithm uses a two staged approach to determine signature values, one stage uses a first random number to calculate the index of the signature value that is to update. The two staged approach improves the accuracy of the produced similarity estimation data for small sized signatures. The two staged approach may further be used to produce random numbers that are related, e.g. each created random number may be larger than its predecessors. This relation is used to optimize the algorithm by determining and terminating when further created random numbers have no influence on the created signature.