Abstract: Described herein are techniques for capturing data from devices to generate replays of sessions of a software application executed by the devices. The techniques use data obtained from the device to determine whether certain events in which a session replay is to be generated have occurred in a session of the software application. When occurrence of such an event is detected during the session of the software application, the techniques determine to trigger collection of session replay data. In this case, the session replay data may be stored and/or transmitted from the device for storage, and subsequently used to generate a session replay. If none of the events are detected, then session replay data may not be transmitted. Accordingly, the techniques can selectively allocate resources (e.g., compute, storage, and/or communication resources) for sessions in which events are detected.

Abstract: In an embodiment, a query system sends compact code to a database service for expansion of the compact code to partially-expanded code and expanded code. In an embodiment, a hash value is generated based on the partially-expanded code and indexed in memory with the expanded code. In an embodiment, a hash value is received as part of a command and expanded code is identified based on the hash value and sent to a database service.

Abstract: The disclosure relates to the field of electric engine digital control domain such as used in the control of vehicle electric motors, including methods related to code handling in the context of debug and/or test and/or calibration or tuning target hardware systems. A method for automated generating of codes, for execution on a heterogeneous hardware system, including software and hardware programmable units, said codes include executable calibration instructions, comprises: (i) loading of initial code, including one or more code descriptions, (ii) providing user calibration instructions, specifying variables in the code descriptions to be considered as calibration parameters and/or monitored values, on said initial code; (iii) a step of automatically generating of said codes, at least one per available unit, based on said loaded initial code, provided with calibration instructions.

Abstract: A method, system and apparatus for software intelligence as-a-service, including decomposing software into functional blocks to provide a software genome, building a representation of the software genome in a knowledge graph linking granularities of the functional blocks, and identifying issues with a target software based on the knowledge graph.

Abstract: A request is received to perform an exploration in a predictive and maintenance service application. A sequence of explorations is added in an evidence package. The evidence package includes the list of micro services. The sequence of explorations in the evidence package are analyzed. Based on the analysis, a user behavior corresponding to the performed exploration is identified. The user behavior is provided as input to the machine learning algorithm. Configuration data corresponding to the exploration and the evidence package is stored in a configuration database. The machine learning algorithm is executed in an execution engine. The execution engine is a micro service. Based on execution of the machine learning algorithm, the list of micro services is automatically identified as recommendations. The list of micro services is displayed as recommendations in the predictive and maintenance service application.

Abstract: Techniques are described herein for pattern identification using enhanced event stream processing. In an embodiment, an event instance is received via a programming interface, the event instance representing an occurrence of a corresponding type of real-world event and comprising one or more variable values pertaining to the occurrence. A ruleset is periodically evaluated as applied to the event instance including, for each of one or more reevaluations of the ruleset as applied the event instance, binding one or more variables of one or more rules of the ruleset to one or more variable values of the event instance and binding one or more other variables of one or more rules of the ruleset to one or more just-in-time variable values, the one or more just-in-time variable values received via one or more programming interfaces in context of the reevaluation.

Abstract: A system that includes a failed test detector and a task updater can automatically update tasks associated with consistent failures of software tests in a software development management platform. The failed test detector can use a set of evidence of test (EOT) files that indicate software testing results over a period of time to identify tests that are consistently failing when executed against versions of a software application. The task updater can automatically create tasks associated with such consistently-failing tests in the software development management platform. The task updater can also automatically close existing tasks associated with tests, in the software development management system, if the failed test detector determines that those tests are no longer failing consistently.

Abstract: A system, method and software product emulate and profile an application playing on a mobile device. The mobile device is emulated using a model based upon characteristics related to performance of the mobile device. The application is played and monitored within the model to determine resource utilization of the application for the mobile device.

Abstract: Systems, methods, and computer-readable media are provided for reusing execution environments and code of serverless functions while ensuring isolation in serverless computing environments. In some examples, a method can include, in response to a first request to run a serverless function, executing, at an execution environment on a network, computer-readable code configured to perform the serverless function; after the computer-readable code has executed, modifying a pointer to an area of memory used to store a first state of the serverless function to reference a different area of memory; in response to a second request to run the serverless function, reusing, at the execution environment, the computer-readable code to perform the serverless function; and based on the pointer referencing the different area of memory, using the different area of memory to store a second state of the serverless function.

Abstract: A query plan includes steps to implement a query and debug steps interleaved among the steps. An execution engine of a database system executes each step of the query plan to realize the query. The execution engine executes each debug step of the query plan to generate debugging information for the step preceding the debug step within the query plan. The debugging information is queryable.

Abstract: Systems and methods for alerting administrators of a monitored digital user experience include performing inline monitoring of network access between one or more users each with an associated user device executing an agent application, the Internet, and one or more cloud applications and private applications. The systems and methods also include obtaining device, application, and network metrics related to the inline monitoring from a cloud system and a logging and analytics system. The systems and methods further include comparing the metrics to one or more alerts comprising alert rules. The systems and methods yet further include sending a notification to one or more administrators when the metrics include data that satisfies the alert rules of the one or more alerts.

Abstract: A method for generating an output for performance impact assessment of a change includes determining changes associated with a first managed computer system where corresponding change records includes a respective change time-stamp, determining performance values for a performance metric for predetermined times and associating respective performance time-stamps, selecting one of the changes wherein the selected change has a change time-stamp, identifying first performance values with performance time-stamps that are prior in time to change time-stamp and associating them with a before-change category, identifying second performance values with performance time-stamps that are later in time relative to the change time-stamp and associating them with an after-change category, and generating an output with the first and second performance values (in a tabular or common timeline format) with the first performance values being distinguishable from the second performance values to thereby allow the user to determin

Abstract: In some embodiments, the present disclosure describes a method that includes at least: receiving, by a processor, audience data identifying candidate audience for a website content; generating a plurality of audience groups based on the audience data; receiving user identifying data of a user; generating personalized online content for the user; tagging the personalized online content with a plurality of dynamic tokens to form trackable personalized online content; transmitting instructions to display the trackable personalized online content on a screen of a computing device; receiving user activity tracking data; training a machine learning algorithm, based on the user activity tracking data, to obtain a trained machine learning content recommendation engine; and utilizing the trained machine learning content recommendation engine to identify updated trackable personalized online content based on a plurality of markups to the trackable personalized online content.

Abstract: In one embodiment, a network assurance service that monitors a network detects an anomaly in the network by applying an anomaly detector to telemetry data collected from the network. The service sends first data to a user interface that causes the interface to present the detected anomaly and one or more candidate root cause metrics from the telemetry data associated with the detected anomaly. The service receives feedback regarding the candidate root cause metric(s) and learns a root cause of the anomaly as one or more thresholds of the candidate root cause metric(s), based in part on the received feedback regarding the candidate root cause metric(s). The service sends second data to the user interface that causes the user interface to present at least one of the candidate root cause metric(s) as a candidate root cause of a subsequent detected anomaly, based on the learned threshold(s).

Abstract: Aspects of the present disclosure can provide a data processing method, apparatus, and medium. The data processing method is applied to a terminal and can include obtaining a data-to-be-processed through an integrated circuit on the terminal, sending the data-to-be-processed to an application processor of the terminal, and processing, by the application processor, the data-to-be-processed and generating a result data.

Abstract: An apparatus includes circuitry configured to maintain a record of a plurality of owners and at least one test operation owned by an owner; prompt automatically the owner in response to a failure of the one test operation; maintain a log of actions taken on the one test operation, and provide availability to the log of actions; update an estimated time to completion, and notify a management entity of the updated estimated time to completion; mark and prioritize an order related to the one test operation, in response to the estimated time to completion being within a threshold of a delivery date; rank the marked order with other marked orders by a risk of not being able to meet the delivery date; and notify the owner of the ranking with an urgent message, in response to the marked order failing to meet the delivery date.

Abstract: Various examples are directed to systems and methods for testing software. A testing system may use test case data describing a first test case failed by a first build of the software application, the first build generated by a first commit operation of the plurality of commit operations to execute a fault localization operation, the fault localization operation to identify a first suspect program element of a first build. The testing system may use the first suspect program element and commit data to select a second commit operation from the plurality of commit operations. The testing system may determine an error-inducing commit operation from the plurality of commit operations and executing a corrective action.

Abstract: Disclosed herein are system, method, and computer-readable medium embodiments for providing the ability to automate the process of generating load tests used for benchmarking APIs. Rather than having to manually generate load tests for a web service API, a test developer can interact with a test service through a web browser and provide the service an API specification and testing parameters. The test service can analyze the API specification, automatically identified endpoints of the API, and generate load tests according to the expected input/output structures of the endpoints. The automatic load test generation can proceed by referring to a library of test instructions and extracting the portions of the test instructions that work for the identified endpoints.

Abstract: Methods, apparatuses, and computer program products are described. A system may run a set of Automated Structure processing (ASP) scripts on a program binary executable written in C-language without making changes to source-code. The system may generate a set of dictionary files indicating data structural information specifically for the C-language program based on running the set of ASP scripts on the program binary executable. The dictionary files may include a list of C-structures referenced and type definitions and structure layouts associated with the C-structures. The system may combine the data structural information with an ASP library to generate an extended ASP library, and may augment the program binary executable with the extended ASP library to generate an augmented program binary executable. The system may programmatically perform an introspection and data discovery procedure on a C-language program at run-time using the augmented program binary executable.

Abstract: A system can be configured to receive an onboarding request for a service and an API associated with the service. An API configuration defining access permissions, API call structures, and available operations can be determined for the service by an onboarding service. The API configuration can be utilized by the onboarding service to register the API with a proxy server such that incoming API calls are redirected to an access endpoint associated with the service. The proxy server enables the service and the API to be updated via the onboarding requests as service modification and API modification can be submitted, validated, and integrated into a service environment due to the proxy server decoupling the API from the service.

Abstract: Systems and methods for automatically generating a secure image with a reduced or minimal set of system calls (syscalls) required by an application to run. A method includes the steps of receiving as input a configuration file specifying one or more image parameters to vary; generating a set of one or more unikernel images, or experiment images, each unikernel image including a specification of how to build the image and how to run the image, each unikernel image based on one of the one or more image parameters; populating a run queue with the one or more unikernel images; and iteratively: executing each of the one or more unikernel images in a host virtual machine; and monitoring, at run-time, a usage of syscalls in the executing image to identify syscalls actually used at any point in time during the executing.

Abstract: Systems, apparatuses, and methods related to managing memory objects are discussed. An example method can include monitoring a first characteristic set for each of a plurality of memory objects written to a first memory device or a second memory device; monitoring a second characteristic set for each of the plurality of memory objects; monitoring a performance characteristic set for the first memory device and the second memory device, wherein the first memory device and the second memory device comprise different types of memory media; and writing each of the plurality of memory objects in a particular respective location of the first memory device or the second memory device based, at least in part, upon the first characteristic set, the second characteristic set, and the performance characteristic set.

Abstract: A system and a method for automatically testing software builds. The system includes testing a first software build using a test package. The test package includes at least a test strategy, a test case, a test model, an automation test script, a crowdsource script, and a manual test script. Further, baseline data is generated based upon a successful execution of the test package on the first software build. Further, a second software build is tested using the test package. Subsequently, the target data is generated based upon an execution of the test package on the second software build. The system then identifies a change in the second software build by comparing the target data with the baseline data. Further, a modification is recommended to the test package for the second software build using Artificial Intelligence (AI) techniques and Natural Language Processing (NLP).

Abstract: A data mining technique is used to find large frequently-occurring source code patterns from methods/APIs that can be used in code development. Simplified trees that represent the syntactic structure and type and method usage of a source code fragment, such as a method, are mined to find closed and maximal frequent subtrees which represent the largest frequently-occurring source code patterns or idioms associated with a particular type and method usage. These idioms are then used in an idiom web service and/or a code completion system to assist users in the development of source code programs.

Abstract: Systems/techniques for facilitating proxy objects for tracking processing of electronic coupon codes are provided. In various embodiments, a system can determine that a browser is performing a checkout on a frontend website. In various aspects, the system can cause the frontend website to instruct the web browser to transmit a validation request to a backend server, wherein the validation request identifies a coupon code and requests that the backend server determine whether the coupon code is applicable to the checkout. In various instances, the system can cause the web browser to append a proxy object to the validation request, wherein the proxy object fetches, during execution of the validation request by the backend server, an execution status of the validation request. In various cases, the system can receive, from the proxy object, the execution status and can initiate one or more electronic actions based on the execution status.

Abstract: A pipeline (e.g., a DevOps or DevSecOps pipeline) may include utilities corresponding to stages within the pipeline. A device may execute the pipeline on a version of a codebase, where the version of the codebase is associated with an immutable identifier of a version control management system. The device may generate metadata for one or more of the utilities of the pipeline based executing the pipeline on the version of the codebase. The device may store the metadata at a database, where the immutable identifier is designated as a primary key for the stored metadata. The device may verify the metadata at one or more gates of the pipeline based on a comparison of the stored metadata to a set of policy information associated with the one or more gates.

Abstract: Concepts for creating a mock for an integration flow are presented. One example comprises analyzing a response to each of a plurality of requests from an integration flow and determining whether or not an identifying property of each of the plurality of requests is present in the response. The method then comprises, responsive to determining that the identifying property is present in the response, generating a mock with an associated matcher based on the plurality of requests.

Abstract: Techniques are described for integrating prediction capabilities from data management platforms into applications. Implementations employ a data science platform (DSP) that operates in conjunction with a data management solution (e.g., a data hub). The DSP can be used to orchestrate data pipelines using various machine learning (ML) algorithms and/or data preparation functions. The data hub can also provide various orchestration and data pipelining capabilities to receive and handle data from various types of data sources, such as databases, data warehouses, other data storage solutions, internet-of-things (IoT) platforms, social networks, and/or other data sources. In some examples, users such as data engineers and/or others may use the implementations described herein to handle the orchestration of data into a data management platform.

Abstract: A service testing system is disclosed to enable consistent replay of stateful requests on a service whose output depends on the service's execution state prior to the requests. In embodiments, the service implements a compute engine that executes service requests and a storage subsystem that maintains execution states during the execution of stateful requests. When a stateful request is received during testing, the storage subsystem creates an in-memory test copy of the execution state to support execution of the request, and provides the test copy to the compute engine. In embodiments, the storage subsystem will create a separate instance of execution state for each individual test run. The disclosed techniques enable mock execution states to be easily created for testing of stateful requests, in a manner that is transparent to the compute engine and does not impact production execution data maintained by the service.

Abstract: A distributed system including multiple processing nodes. The distributed system can perform certain acts. The acts can include receiving a set of input nodes and a set of criteria. The acts can include obtaining an adjacency list representing a large connected component. The large connected component can include nodes, edges, and edge metadata. A quantity of the nodes of the large connected component can exceed 1 billion. The adjacency list can be distributed across the multiple processing nodes. The nodes of the large connected component can include the input nodes. The acts also can include performing one or more iterations of traversing the large connected component until a stopping condition is satisfied.

Abstract: A system includes one or more code development servers operable to monitor development of code files and one or more code execution servers operable to execute the code files. One or more code analysis tools of the system include instructions that when executed by at least one processing device result in collecting code development data associated with development of the code files on a per user basis and determining a predicted code execution performance score of one or more selected files of the code files based on the code development data. One or more resources of the one or more code execution servers associated with execution of the one or more selected files are predictively allocated based on a predicted code execution performance score. One or more code execution metrics are captured associated with executing the one or more selected files on the one or more code execution servers.

Abstract: A system may be disclosed in the present disclosure, comprising: an interface service unit configured to perform at least one of sending data to or receiving data from one or more users via a user interface; and a transmission unit including: a blockchain adaptor configured to transmit data to a plurality of different types of blockchains, via a blockchain interface, according to data format and communication mode requirements of each of the plurality of different types of blockchains and a transmission controller configured to trigger a smart contract running on a blockchain of the plurality different types of blockchains via the blockchain interface, and control a data transmission under instructions from the smart contract, wherein the data transmission is based on data received from the user interface.

Abstract: A database service that receives and manages data into columnar databases. Individual columnar databases or columnar database partitions are associated with a dictionary that provides an encoding for the data in the columnar database. The database service generates count information for the dictionary entries. The database service also maintains one or more augmented dictionary values that correspond to featurization criteria. The database service applies the augmented dictionary values to respond to requests for feature data.

Abstract: A code reuse processing method, apparatus and electronic device related to a software development technology in the technical field of computers. The method includes: receiving a target request sent by a client of a target unit; in response to the target request, determining a first code line quantity per capita submitted within a target unit time and a reuse code base of the target unit used by a first code base in a dependency manner, the first code base is a code base except the reuse code base; determining reference information configured to indicate an amount of labor capable of being saved for the target unit when the target unit performs a code reuse within a target duration, the reference information based on the first code line quantity, a code line quantity of the reuse code base and a preset reuse proportion; and outputting the reference information to the client.

Abstract: A computer-implemented method, non-transitory, computer-readable medium, and computer-implemented system are provided for deploying a smart contract in a blockchain network. The computer-implemented method includes: receiving, by a blockchain node in a blockchain network, a transaction for creating a smart contract, wherein the transaction comprises a machine code of the smart contract, and the machine code of the smart contract is obtained by Ahead of Time (AoT) compilation of a bytecode of the smart contract in a first trusted execution environment (TEE); determining, by the blockchain node, that the machine code of the smart contract is obtained in a trusted TEE; and in response to determining that the machine code of the smart contract is obtained by the trusted TEE, completing, by the blockchain node, a deployment of the smart contract.

Abstract: Disclosed herein is an information processing apparatus, comprising: a memory configured to store program code; and electric circuitry including a processor, the processor being configured to read and operate according to the program code, the electronic circuitry configured to: set a plurality of candidate values of a parameter tunable in a computer system; trial each of the plurality of set candidate values of the parameter to the computer system for a predetermined period of time or a predetermined number of times and to calculate a reward in the computer system; select, when a trial satisfies a predetermined termination criterion, a candidate value of the parameter for which the maximum reward is calculated among the candidate values of the parameter and apply the selected candidate value of the parameter to the computer system; and re-set candidate values of the parameter based on the selected candidate value of the parameter to repeat.

Abstract: Systems, methods, and software products, determine permission profiles for computer executable functions (functions). The systems, methods and software products, utilize both static analysis and dynamic analysis, in order to determine the minimal set of permissions based on the inter-relations between these two analysis methods, i.e., static analysis, and dynamic analysis, to determine the permission profiles for computer executable functions (functions).

Abstract: 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.

Abstract: In some embodiments, a method receives a query to retrieve data from a source table and insert the data into a target table and allocates a size of memory. A portion of the data from the source table is retrieved based on the size of memory and stored in the memory. Then, the method stores the retrieved portion of the data stored in the memory into the target table and continues to retrieve portions of data from the source table in increments based on the size of memory, store the retrieved portions of data in the memory, and store the retrieved portions of data from the memory in the target table until the data from the source table has been inserted into the target table.

Abstract: A system and method detect and forecast a performance degradation of a M-system. The method includes collecting data regarding the M-System during a period of time P1, storing the collected data in a database and analyzing the collected data collected during the period of time P1 by an elaboration routine containing two distinct elaboration phases. Namely, a first elaboration phase, where a performance analysis system selects among the collected data a set of data to be analyzed and removes any noisy data from the set of data and a second elaboration phase, where the performance analysis system correlates, for the set of data, data belonging to different sources, but generated at a same time within the period of time P1 to create M-System state data snapshots characterizing the M-System at different times Ti within the period of time P1. Finally, a model for the M-System is generated from input datasets.

Abstract: Techniques for evaluating software systems are provided, including measurement of performance ratings of features of an app-under-test are described. The evaluation may include analysis of a video recording of the user interface of the app-under-test, where the video analysis may include comparing the changes over time of co-located pixel in the video to produce a performance rating, for example a speed index. The results of multiple such tests can be compared by comparing the performance rating produced during execution of different tests.

Abstract: Systems and methods for operating a focal plane array are provided. The operations can be stored as command sequences stored in a command queue established in memory provided as part of reconfigurable focal plane electronics. Each command sequence can include definitions of a plurality of image frames that are executed in series. The configurations of the defined frames can be the same as or different from one another. Moreover, the frame definitions can specify a number of focal plane array parameters, such as gain, full frame or window, and integration time. The sequence of focal plane array parameters can be provided to the focal plane array as a command stream at the direction of a state machine implemented by the reconfigurable focal plane electronics. New commands containing different frame commands can be loaded into the command queue without requiring reconfiguration of the electronics.

Abstract: Technologies are shown for HGM based control for smart contract execution. HGM control rules control function calls at a system level utilizing function boundary detection instrumentation in a kernel that executes smart contracts. The detection instrumentation generates a call stack that represents a chain of function calls in the kernel for a smart contract. The HGM control rules are applied to HGMs collected from the call stack to allow or prohibit specific HGMs observed in functions or function call chains. HGM control rules can use dynamic state data in the function call chain. If the dynamic state data observed in function call chains does not meet the requirements defined in the HGM control rules, then the function call can be blocked from executing or completing execution. The HGM control rules can be generated by executing known sets of acceptable or vulnerable smart contracts and collecting the resulting HGMs.

Abstract: A data mining technique is used to find large frequently-occurring source code patterns from methods/APIs that can be used in code development. Simplified trees that represent the syntactic structure and type and method usage of a source code fragment, such as a method, are mined to find closed and maximal frequent subtrees which represent the largest frequently-occurring source code patterns or idioms associated with a particular type and method usage. These idioms are then used in an idiom web service and/or a code completion system to assist users in the development of source code programs.

Abstract: An apparatus includes a memory and a processor. The processor collects from a database server, statistics indicating a performance of the server. The processor applies to the statistics, a machine learning algorithm configured to identify, based in part on the statistics, one or more issues affecting the performance of the database server. Applying the machine learning algorithm includes applying to the statistics, a regression algorithm trained to identify one or more candidate issues. Applying the machine learning algorithm also includes applying to the one or more candidate issues, a classification algorithm trained to classify each candidate issue as an issue of the one or more issues or a false positive. The processor additionally generates a script that, when executed, remediates the candidate issues of the one or more candidate issues classified by the classification algorithm as the issues of the one or more issues. The processor further executes the script.

Abstract: Methods, apparatus, systems and articles of manufacture to recommend instruction adaptations to improve compute performance are disclosed. An example apparatus includes a pattern detector to detect an execution pattern from an execution profile provided by a server, the execution profile associated with an instruction stored in an instruction repository. An adaptation identifier is to identify a possible instruction adaptation that may be applied to the instruction associated with the execution pattern. A model processor is to predict, using a machine learning model, an expected performance improvement of the adaptation. A result comparator is to determine whether the expected performance improvement meets an threshold. An instruction editor is to, in response to the result comparator determining that the expected performance improvement meets the threshold, apply the possible instruction adaptation to the instruction in the instruction repository.

Abstract: Methods and systems for updating configurations. An application can be determined to be incorrectly configured. A request can be sent to update a configuration property. The configuration property can be updated in a test environment. The application can be tested with the updated configuration property in the test environment. The test of the application with the updated configuration property in the test environment can be identified as successful. An incorrect configuration of the application can be updated.

Abstract: A method at a computing device for identification post compilation manipulation of a binary image, the method including assessing the binary image for at least one junk instruction set; determining that the at least one junk instruction set is found within the binary image; and flagging the binary image as being manipulated based on the determining.

Abstract: Performing a targeted partial recording of an executable entity includes executing the executable entity at a processor. While executing the executable entity, it is determined that a target chunk of executable instructions are to be executed as part of the execution of the executable entity. Each input to the target chunk of executable instructions is identified, including identifying at least one non-parameter input. A corresponding value for each identified input is recorded into a trace, along with information identifying the target chunk of executable instructions.

Abstract: Systems and methods for remote mobile development and test feedback are disclosed. According to one embodiment, in an electronic device testing apparatus comprising at least one computer processor, a method for remote mobile development and test feedback may include: (1) receiving a test request comprising one or more tests to conduct on at least one electronic device in a device farm; (2) parsing the one or more test requests to identify the features to be tested; (3) identifying one or more test scripts that encompasses the features to be tested; (4) identifying a required software configuration on the at least one electronic device to conduct the one or more test; (5) installing the required software configuration on the at least one electronic device; (6) executing the test features; and (7) storing results of the test features.