Abstract: A historian interface system provides a graphical representation of tags that represent attributes of a continuous process. A historian system stores the tags and metadata values describing the tags. A display device coupled to the historian system via a communication network displays graphical representations of the tags via display panels and receives selections of the tags. The historian system contextualizes selected tags based on the metadata values describing the selected tag and determines an optimal visualization scheme for the selected tags. The display device displays graphical representations of values of the tags and dynamically determines optimal grouping of the tags based on properties of the display device.

Abstract: By analyzing a test case in a set of test cases, the test case is classified into a test type. Using a result of analyzing a test execution environment, a flake parameter is set, the flake parameter comprising an execution environment characteristic capable of causing an inconclusive result of execution of the test case. Responsive to determining that the test type maps to the flake parameter, the test case is removed from the set of test cases, the removing resulting in a filtered set of test cases, the determining performed using a predefined set of mappings. The filtered set of test cases is executed in the test execution environment.

Abstract: Methods, systems, and computer-readable media for debugging and profiling of machine learning model training are disclosed. A machine learning analysis system receives data associated with training of a machine learning model. The data was collected by a machine learning training cluster. The machine learning analysis system performs analysis of the data associated with the training of the machine learning model. The machine learning analysis system detects one or more conditions associated with the training of the machine learning model based at least in part on the analysis. The machine learning analysis system generates one or more alarms describing the one or more conditions associated with the training of the machine learning model.

Abstract: The embodiment may include a computing device that identifies a software code. The embodiment may determine an attribute access and a method call. The embodiment may inject instrumentation code to the software code to capture the attribute access and the method call. The embodiment may convert an attribute into a value using a conversion method based on determining, during an execution of the software code, that the attribute access failed. The embodiment may create a mock object and uses the mock object as a result of the method call to continue execution of the software code based on determining, during the execution of the software code, that the method call failed.

Abstract: An electronic product testing system includes: a product testing device having a processing unit configured to execute an electronic file to perform testing of a product based on product testing instruction in the electronic file; wherein the processing unit is configured to perform the testing of the product by performing a machine-testing action based on the product testing instruction in the electronic file; wherein the electronic file comprises hand-off instruction; and wherein the processing unit is also configured to generate a request for a human-testing action to be performed by a human-tester based on the hand-off instruction in the electronic file.

Abstract: During software development, embodiments find various kinds of weak spots in source code and automatically suggest fixes to strengthen the code, without requiring developers to expressly select weakness finder mechanisms or fixer mechanisms by navigating a development tool's menu system. Weakness finders may analyze code using items such as hole detection, diagnostic errors, test results, changed code matches, prospective code discrepancies, generated code confidence scores, generated suggestion competition, and artificial intelligence. Weak spots and their context are submitted to weak spot fixers, which may generate fix suggestions using functionalities such as code synthesis, refactoring, autocompletion, retesting, and artificial intelligence. Fix candidate sets may be evaluated for consistency, diagnostic errors, and discrepancies. Snippets may be dynamically filled for presentation to a user.

Abstract: A system to detect and resolve conflicts between different experiments running on a website building system (WBS). The system includes at least one processor, a conflict resolver to check for interactions and conflicts between an experiment and at least one other existing experiment from a set of existing experiments in the WBS, when the experiment is set-up or integrated into the set of existing experiments. The conflict resolver either resolves the interactions and conflicts, or allows the interactions and conflicts to remain. The system also includes an experiment manager running on the at least one processor to manage and coordinate the experiment and the at least one other existing experiment when the experiment is running concurrently with the at least one other existing experiment, after set-up or integration of the experiment.

Abstract: Client systems of a distributed database system manage execution of transactions on data stored within the distributed database system. The client systems communicate directly with database nodes of the distributed database system in order to manage transactions. The client systems interact with the database nodes of the distributed database system via a client-side interface that performs various operations to execute transactions at the distributed database nodes, including retrieving records, staging mutations or insertions, committing mutations or insertions, or rolling back mutations or insertions on records stored on the distributed database nodes. Interactions between the client-side interface and the database nodes of the distributed database system are further configured to prevent conflicts between different transactions executed by the same or different client systems at the database nodes.

Abstract: A system and method for generating a set of instructions for static analysis, for application code utilizing an external initialization engine. The method includes receiving a result from a code hook, the code hook inserted into an application code at an anchor point, the application code deployed in a cloud computing environment, wherein the application code requires an external initialization framework; and generating a set of instructions based on the received result and the anchor point of the application code, in response to emulating execution of the application code.

Abstract: A monitoring system includes storage, and one or more processors. The storage stores at least one of first output data that is obtained from a learning model, or first statistical information that is obtained from the first output data. The processors calculate a degree of abnormality indicating a degree of change in statistical information of second output data with respect to the first statistical information, or a degree of change in the statistical information of the second output data with respect to second statistical information. The processors determine whether or not there is occurrence of an abnormality in the learning model, on the basis of the degree of abnormality. The processors output information indicating occurrence of the abnormality, in a case where occurrence of the abnormality is determined.

Abstract: Described herein are techniques that may be used to automate testing of services on mobile devices using visual analysis. In some embodiments, a machine learning model is trained using interaction data received from a number of mobile devices by correlating user selections with visual elements (e.g., icons). During execution of a testing routine on a mobile device, screenshots are obtained of a screen of the mobile device and provided to the machine learning model. An action is generated based on the provided screenshot that simulates a user action (e.g., a user touch on the screen of the mobile device) at a location of an icon or other visual element associated with the testing routine. These steps are repeated until an end-state of the testing routine is detected.

Abstract: An approach for assisting software developers to fill the data gap and reproducing client application issue using reported reproducing steps is disclosed. The approach involves constructing service request/response sequence (from the developer's side based on the limited data) from customer's reproducing steps and developer's running inspection result and perform UI-service mapping, redirecting service call to data simulator which replay the service request and response, and adjusting service response with multiple data sources and policies. Lastly, the approach can transform the issue to an automatic test script with the service response in a mockup function (e.g., can be used to extend test data and enhance test cases).

Abstract: An error revision suggestion method for customized software integration applications may comprise storing a plurality of customized software integration applications for specific integration processes for transforming data to enable electronic data exchange, generated from a customized visual model with a plurality of visual modeling elements representing customized executable code sets. The method may further comprise transmitting an executable run-time engine for a first of the plurality of customized software integration applications and a first customized code set for execution at a specific user business process system, receiving an indication an error has occurred during execution of the first customized code set, and transmitting an instruction to the user indicating a correction to erroneous user input is required to resolve the error if the error is associated in a resolve database with a previously executed correction to erroneous user input.

Abstract: A method may include first executing an operation of an application using a function call of a first version of a package of the application; first detecting, by the application, an error in the first executing; in response to the first detecting, second executing the operation of the application using a function call of a second version of the package of the application; second detecting, by the application, that no error occurred during the second executing; and in response to the second detecting, electronically logging an error with respect to the function call of the first version of the package.

Abstract: Disclosed is a method of efficient testing by selective UI interaction, through test script sections including setup, execution and verification, applied to an AUT that operates in both API mode and UI)mode, including providing a test environment that, when testing the UI mode of the AUT, defaults to ignoring the UI mode during setup and supplying setup values stored in a file directly to an API without rendering or interacting with UI elements in the setup section of the script. The method includes encountering an override directive in the setup section of the test script, which mandates interaction with a specified UI element in the setup section, and responsive to the directive, overriding of the default of ignoring the specified UI element in the setup section, rendering the specified UI element, and applying a bot to interact with and supply setup values from the file to the specified UI element.

Abstract: A method of populating a test environment for integration testing of a production database. The production database includes a plurality of tables, and may be represented by a directed acyclic graph (DAG), in which each of the plurality of tables is represented by a respective node of the DAG and schema-level constraints of the plurality of tables are represented by edges of the DAG. The method may involve constructing the DAG, topologically ordering the plurality of tables of the production database according to the DAG, randomly generating test data in accordance with the schema-level constraints of the plurality of tables, and populating the randomly generated test data to the test environment according to the topological ordering of the plurality of tables.

Abstract: Methods and apparatuses are described for testing and deploying targeted versions of application libraries within a software application. A computing device selects a software application comprising application libraries each associated with a current version identifier. The computing device identifies a target version of one or more application libraries, the target version associated with a different version identifier than the current identifier. The computing device defines a software application build for the software application incorporating the identified target versions of the application libraries, and deploys the application build to a test computing environment. The computing device executes tests of the software application build in the test environment, and captures test execution data for the target versions of the libraries in the software application build.

Abstract: An algorithm and method for automatically generating test vectors for an LRU by deriving test vectors at the LRU boundary that, when simulated on the LRU, reproduce input and output of given test cases at the boundary of the individual requirements, and for knowing whether there are test cases that cannot be realised, i.e. test vectors cannot be derived at the LRU boundary to reproduce them at the boundary of individual requirements.

Abstract: A debug information abstraction unit (32) of a proxy server (30) adds, when a predetermined rule of an extension program is embodied into a program, a program for outputting debug information regarding the predetermined rule to the embodied program. Then, a debug information transmission unit (41b) of a terminal device (40) transmits, to a debug support device (10), the debug information regarding the predetermined rule for which the program has been added.

Abstract: A transient input/output in progress state is established during processing of a testcase by a test infrastructure in a computing environment. The method includes obtaining the testcase for an object having one or more pages, and processing the testcase by the test infrastructure. Processing the testcase by the test infrastructure includes, for a page of the object, generating a delay in the processing of the testcase for the page of the object. The delay opens a transient input/output in progress state during which one or more test operations reference the page of the object.

Abstract: Randomized testing can be used to explore a set of possible transactions, schemas, and system states, including partionings, which can exist in a distributed database. The tests can be complementary to other system failure, performance, and version compatibility tests. Randomly generated transactions can be computed or evaluated at a transactor and compared to results derived from a transactor emulator.

Abstract: To facilitate runtime monitoring and analysis of an application without modifying the actual application code, an agent monitors and analyzes an application through detection and evaluation of invocations of an API of a runtime engine provided for execution of the application. The agent registers to receive events which are generated upon invocation of target functions of the runtime engine API based on its load. Once loaded, the agent initially determines the language and language version number of the runtime engine. The agent determines associations of events for which to monitor and corresponding analysis code to execute upon detection of the invocations based on the language and version number information. When the agent detects an event during execution of the application based on invocations of the runtime engine API, the agent can monitor and analyze execution of the application based on execution of analysis code corresponding to the detected event.

Abstract: A method of testing a change in a software code includes, searching a database of tests to identify a subset of the tests that include a function that executes the change, forming, from the subset, a multitude of groups each having a different execution path. The tests in the same group have the same execution path. The method further includes prioritizing the tests within each of the multitude of groups based on one or more testing characteristics, and selecting, from each of the groups, one or more of the prioritized tests to test the change.

Abstract: A technology management server for domain-based technology deployment and management is provided. The server includes a processor configured to receive an architecture definition file identifying a prior system status for each snapshotted application system. The processor is also configured to scan the application systems and classify each of the scanned application systems into an associated technology domain using a domain classification algorithm. The processor is configured to identify each scanned application system with a changed system status. The processor is configured to obtain a system update for each scanned application system with a changed system status, based on the technology domain. The system updates define implementation characteristics of each changed scanned application system. The processor is also configured to redefine the architecture definition file with the system updates.

Abstract: A data system is provided for analyzing and maintaining data obtained from one or more data sources on which the data system depends. The system includes a primary database including current values used by the system and a collection of executable algorithms used to generate the data maintained in the primary database. In response to receiving a notification regarding a change in one of the data sources, a dependency database is used to establish an execution order for algorithms of the algorithm collection that are directly or indirectly dependent on the changed data. The algorithms identified in the execution order are then executed in accordance with the execution order and the corresponding result is stored in the primary database. The system may include data harvesters adapted to recognize changes in the data sources and to generate and transmit corresponding change notifications when such changes occur.

Abstract: Techniques are provided for updating, managing, and maintaining a reference template for web service API testing. A plurality of logs, corresponding to a target application that provides one or more web services, may be captured. The captured logs may be filtered using information (e.g., URL extension) in the captured logs. Each filtered log may be parameterized and API request payload data may be extracted to generate a baseline template. A reference template may be compared with a corresponding baseline template to determine if they differ. If they differ, a test template may be generated by replacing each differing field of the reference template with a corresponding baseline template identifier. The test template may then be used in testing a web service API, such that a test template can conform with a changing web service API.

Abstract: A method of simulating codes that form a program configured to control a control target includes causing a processor to execute the following: first-setting a first process of executing a simulation of an operation of a code group excluding a specific code among the codes; second-setting a second process of executing a simulation of an operation of a specific model obtained by modeling the specific code; first-simulating, in the first process, a first simulation of a code preceding the specific code in the code group; second-simulating, in the second process, a second simulation of the specific model through use of an execution result of the first simulation by inter-process communication between the first process and the second process; and third-simulating, in the first process, a third simulation of a code succeeding the specific code through use of an execution result of the second simulation by the inter-process communication.

Abstract: An example method for visual testing and issue communication of programmed display of content includes obtaining a workflow of test scenarios for visual testing a display. The content displayed on the display is controlled by a set-top box (STB) device executing target instructions. The example method further includes identifying a visual testing issue associated with executing the test scenarios, and communicating the workflow and issue to a remote device for reproduction of the issue.

Abstract: A method, system and product for automated quality assessment of a programming task. Programming activity of a developer is monitored to obtain measurements of a plurality of metrics in a plurality of time segments. Functional correctness of the program at a last time segment of the plurality of time segments is determined. Based on the measurements of each of the metrics in the plurality of time segments, a plurality of features are computed. The plurality of features are indicative of a behavior of the developer while programming. A prediction model is utilized to provide an automated assessment based on the values of the plurality of features.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on computer-storage media, for prioritizing test cases. Processes may include obtaining test artifacts that were generated based on testing one or more legacy versions of a software application using multiple test cases, generating a risk index based at least on the test artifacts that were generated based on testing the one or more legacy versions of the software application using the multiple test cases, and training an ensemble model that is configured to identify likely unnecessary or redundant test cases in connection with in testing an updated version of the software application, based at least on the risk index.

Abstract: A method of analyzing source code includes receiving, by a processor, an updated version of a computer program, the updated version including a source code. The method also includes preprocessing, by a compiler, the source code for a target computing platform. Preprocessing the source code by the compiler includes identifying a macro condition associated with one or more computer instructions enclosed by a macro, determining object code corresponding to the one or more computer instructions based on a current value of the macro condition, and generating object code and macro information for output to a debugger, the macro information including one or more breakpoint conditions in the macro.

Abstract: A neural transformer model with attention is trained to predict candidates to complete a line of source code with a zero-inference capability. The model is trained on an unsupervised training dataset that includes features from source code written in multiple programming languages. The features include a file-level context and a local context, where the file-level context includes a global context, a class context, a function context, and/or a method context for each class, function and/or method of the source code programs used in the training dataset. The local context includes method bodies, function bodies, and/or stand-alone code of main method routines. From these features, the model is able to learn to predict an ordered sequence of code elements that complete a line of source code in a programming language seen and not seen during training.

Abstract: A system to support validation and debugging of compiled low-level instructions for a machine learning (ML) network model on an ML-specific hardware. A compiler identifies well-defined boundaries in the ML network model based on primitives used to generate low-level instructions for the hardware. The ML network model is partitioned into units/layers/sub-graphs based on the plurality of well-defined boundaries. The compiler then generates an internal representation for each of the units wherein the internal representation is mapped to components in the hardware. Each of the units is compiled into a first set to be executed on the ML-specific hardware and a second set to be executed on a second computing device. The output results from executing the two sets of low-level instructions are compared to validate the first set of low-level instructions. If the outputs do not match fully, the first set of low-level instructions is debugged and recompiled.

Abstract: Disclosed are a system (100) and a method for an identification of web elements used in an automation test case. The system (100) and the method ensure reliable identification of an object despite dynamism. The system (100) and the method allow a tester to focus on the test case development of test cases rather than object management that in turn increases the success rate and efficiency of the automatic testing. The system (100) and the method track changes in object attributes, structure and behaviour thereby facilitating identification of dynamic objects automatically and correction of the object locator on the fly during test execution.

Abstract: Metric data may be received, where the metric data may include one or more time series, where each time series may include a set of metric datapoints corresponding to a set of time slices, and where each metric datapoint may be a measurement of a metric of a monitored object in an infrastructure. An infrastructure health score may be computed for each time slice in the set of time slices based on the metric data. A machine learning (ML) model may be trained based on metric datapoints corresponding to at least a current time slice and the infrastructure health score corresponding to a future time slice. The trained ML model may then be used to predict a future infrastructure health score based on at least current metric datapoints.

Abstract: A system for determining code ancestry. The system includes: a memory; and a processor communicatively coupled to the memory. The processor is configured to perform a method comprising: receiving a source code file; parsing a plurality of functions out of the source code file; generating fuzzy fingerprints from the plurality of functions; and storing the fuzzy fingerprints in a graph database.

Abstract: A center configured to communicate with an OTA master configured to control software update for electronic control units mounted on a vehicle includes one or more processors. The one or more processors are configured to store security information in which security levels required for the software update are associated with the electronic control units mounted on the vehicle, respectively, and generate a distribution package applied encryption at the security level associated with a target electronic control unit based on the security information. The target electronic control unit is an electronic control unit that is a target of the software update.

Abstract: Methods, apparatuses, and systems are described for artificial-intelligence based techniques for programmatically generating and integrating application programming interfaces (APIs). An example method may include, in response to receiving by one or more processors, an integration data object, processing, by the one or more processors, based at least in part on an integration machine learning model, the integration data object in order to identify one or more integration features associated with the integration data object; programmatically generating, by the one or more processors, based at least in part on the one or more integration features, an application programming interface (API) model corresponding with the integration data object; and generating, by the one or more processors, an API generation data object corresponding with the API model for execution.

Abstract: A method includes decoding, by at least one hardware processor, a notification of a changed database code of a database. A query is executed responsive to the notification. The query indicates a data processing command and a data object in the database. A regression in the changed database code is detected based on multiple regression testing operations applied to the data processing command and the data object. Analysis of the regression is performed to detect a rollout parameter of a plurality of rollout parameters as a root cause of the regression. The plurality of rollout parameters are associated with the changed database code. A determination is made on whether to perform a mitigation action for the regression based on the rollout parameter.

Abstract: Systems and methods for testing components or scenarios with execution history are disclosed. A method may include: receiving, at a testing interface and from an application or program executed by a user electronic device, an identification of a test and one or more data layers of a plurality of data layers in pod to test, the plurality of data layers including a data collection layer, a data ingestion layer, a data messaging layer, a data enrichment layer, and a data connect layer; receiving, by the testing interface, a selection of testing parameters or values for the identified test; retrieving, by the testing interface, the identified test; executing, by the testing interface, the identified test on the identified one or more data layers using the selected testing parameters or values; retrieving, by testing interface, results of the execution of the test; and outputting, by the testing interface, the results.

Abstract: Automated query retry includes selecting a first node of a plurality of nodes of an execution platform in response to a query. The first node is configured with a first version of a database platform. A first execution of the query is performed using the first version of the database platform at the first node. The method further includes detecting the first execution results in a failed execution. A second execution of the query is scheduled. The second execution uses at least one of the first version of the database platform or a second version of the database platform configured at a second node of the plurality of nodes. The second version is released after the first version. A cause of the failed execution of the query at the first node is determined based at least in part on a result of the second execution of the query.

Abstract: Systems, computer program products, and methods are described herein for automated code resolution in an extended reality environment. The present invention allows a user (such as a software developer) to view source code discrepancies in real time using an extended reality (XR) environment. In this regard, the present invention focuses on electronic applications (and the electronic work products/electronic data hosted thereon) and represents a combined view of real-time applications and application requirements within an XR environment. A user may then visualize discrepancies between the current application and the application requirements via an XR platform (accessible using a virtual/augmented/mixed reality device) and proactively make edits, approvals, or otherwise interact with said application. The system may also be configured to automatically alter the source code to resolve said discrepancies.

Abstract: A method of generating a user interface for presentation to a user. The method comprises executing a first application computer program to provide a user interface, executing agent computer program code to interrogate and modify said user interface during execution of said first application computer program, and presenting said modified user interface. The first application computer program may be run on a server, while the modified user interface may be presented to a user at a client connected to said server.

Abstract: The disclosure describes techniques that enable detection of memory leaks of software executing on devices within a computer network. An example network device includes memory and processing circuitry. The processing circuitry monitors a usage of the memory by a software component operating within the network device. The processing circuitry periodically determines a memory growth pattern score for the software component based on the usage of the memory. The processing circuitry also predicts whether the user-level process is experiencing a memory leak based on the memory growth pattern score. The processing circuitry applies confirmation criteria to current memory usage of the software component to confirm that the software component is experiencing the memory leak. When the software component is experiencing the memory leak, the processing circuitry generates an alert.

Abstract: Processor trace systems and methods are described. For example, one embodiment comprises executing instrumented code by a compiler, the instrumented code including at least one call to un-instrumented code. The compiler can determine the at least one call to un-instrumented code is a next call to be executed. A resume tracing instruction can be inserted into the instrumented code prior to the at least one call to the un-instrumented code. The resume tracing instruction can be executed to selectively add processor tracing to the at least one call to the un-instrumented code, and the at least one call to the un-instrumented code can be executed.

Abstract: Various embodiments are directed to performing automated software testing configuration management operations. In one embodiment, a method is provided. The method includes generating a graph data structure including nodes representing test steps across test cases of a software testing data object for a software application platform and including segments each connecting two nodes and representing test cases having the two represented test steps. The method further includes receiving a query describing a testing change and generating extracted features from the query. The method further includes generating test outcome requirements and graph portions of the graph data structure relevant to the testing change using supervised machine learning models and the extracted features.

Abstract: The disclosed technology teaches rejecting, during validation, a sequence of components intended for interacting with a user. Included are providing a sequence setup GUI supporting construction of an executable sequence by connecting at least five components in a directed graph, and tracing multiple paths through the directed graph, including from at least one conditional branch at a first up-chain component, in which down-chain components accept as input and depend on output from at least one up-chain component, referred to as input chain dependencies. Also included are locating at least one error in use of a particular down-chain component when invoked following one of the multiple paths, where the error results from failure to satisfy any of the input chain dependencies of the particular down-chain component, and reporting the error during validation to a user of the GUI, before passing the sequence of components from validation to use in production.

Abstract: An embodiment may involve storage containing incident logs and mappings between incident logs and vector representations generated by a machine learning (ML) model.

Abstract: Embodiments of the present disclosure relate to a method, system and computer program product for semantic search based on a graph database. In some embodiments, a method is disclosed. According to the method, the user jobs of a user are obtained from a first software product. Based on the user jobs, target test cases are selected from a plurality of test cases associated with the first software product and a second software product. The target test cases are applied to the first software product and the second software product, and in accordance with a determination that a result of applying the target test cases satisfies a predetermined criterion, an instruction is provided to indicate migrating from the first software product to the second software product. In other embodiments, a system and a computer program product are disclosed.

Abstract: There are provided systems and methods for a data integration framework that provides an institutional or organizational user data enrichment capability locally. Specifically, instead of relying on the fraud detection platform to constantly updating and/or building new data connectors to intake data from updated or a new data provider, an institutional user, such as a financial institution, may receive a software development kit (SDK) from the fraud detection platform, using which the institutional user may build its own data connector deployed at the institutional user.