Abstract: The disclosed technology teaches testing with a test parameter data structure, applied to an AUT that operates in both API and UI mode, processing a configurable script to test in both modes. UI mode renders and interacts with UI elements utilizing values stored in the structure, used by the script in both modes, providing display mark-up in the script that is rendered in UI mode and formats fields to receive data that map to specific elements, leaving to be completed a mapping connection between the fields in the display and specific elements in the structure. The method includes providing a mapping of fields to elements, based on names, and while processing the script in UI mode, rendering the mark-up from the script, using a bot to interact with and complete the mark-up, applying the mapping to identify elements to complete fields, and causing processing of the fields in the mark-up.

Abstract: In some implementations, there is provided a method including determining whether a topology description includes a static physical host name and a static port address; in response to determining the topology description includes the static physical host name and the static port address, converting at least the topology description into a deployment file; including, in a container, the deployment file, code, and a control script that limits pre-start database operations to a single node of a plurality of nodes of a cloud platform; and deploying, the container including the deployment file, the code, and the control script, to the cloud platform to form, at the cloud platform, the plurality of nodes including the single node. Related systems and articles of manufacture are also disclosed.

Abstract: Methods and systems for test deployment of computational code on virtual servers are disclosed. In one embodiment, an exemplary method comprises receiving test computational code programmed to provide resources; selecting a test virtual server from a plurality of virtual servers; uploading the test computational code to the test virtual server; initializing the test computational code on the test virtual server; receiving computational performance measurements of the test virtual server and a remainder of the plurality of virtual servers; calculating a test score of the test virtual server based on the received computational performance measurements; and stopping the test computational code if the test score is outside a set range.

Abstract: Normal virtual machine operation is observed to automatically determine patterns of resource utilization. Backup activities are then scheduled, taking into account these utilization patterns. For example, if a normally scheduled backup would occur during a busy period, it may be rescheduled to a less busy period. As another example, backups made by made opportunistically during less busy periods even if not required by the normal backup schedule, in order to alleviate backup demands during more busy periods.

Abstract: Automated patch compatibility testing systems, methods, and computer program products are disclosed. The automated compatibility testing systems, methods, and computer program products disclosed herein enable an entity to check the functionality of applications following patches applied to an original image so that the enterprise can determine how its target computing systems will react to such patches before those patches are actually installed/deployed to the target computing systems. The automated compatibility testing systems, methods, and computer program products disclosed herein helps enterprises ensure that patches do not adversely impact the target computing systems and the operations thereof, and enable the enterprise to operate with minimal disruptions, stay current with patches, and take proactive and informed business decisions in managing the enterprise's computer infrastructure.

Abstract: A method for testing a system under test (SUT) in an active environment to identify cause of a soft failure includes recording a first difference vector by executing a set of test cases on a baseline system and monitoring performance parameters of the baseline system before and after executing the test cases. Each performance record represents differences in the performance parameters of the baseline system from before and after the execution of a corresponding test case. The method further includes, similarly, recording a second difference vector by executing the test cases on the SUT and monitoring performance parameters of the SUT before and after executing the test cases. The method further includes identifying an outlier performance record from the second difference vector by comparing the difference vectors and further, determining a root cause of the soft failure by analyzing a test case corresponding to the outlier.

Abstract: A system for automated malicious software detection includes a computing device, the computing device configured to receive a software component, identify at least an element of software component metadata corresponding to the software component, determine a malicious quantifier as a function of the software component metadata, wherein determining the malicious quantifier further comprises obtaining a source repository, the source repository including at least an element of source metadata, and determining the malicious quantifier as a function of the at least an element of software component metadata and the at least an element of source repository metadata using a malicious machine-learning model, and transmit a notification as a function of the malicious quantifier and a predictive threshold.

Abstract: A system and method determines a unique performance benchmark for specific computer object code for a particular microprocessor. By generating multiple unique benchmarks for a single, same code module on multiple different processors, the method determines which processor is optimal for the code module. By generating for a single designated processor a performance benchmark for each code modules of multiple modules, where the multiple modules have a same/similar functionality but variations in detailed code or algorithms, the system and method identifies code variation(s) which is/are optimal for the single designated processor. The system and method may entail first extracting selected features of object code (as actually executed) into a code profile, and then generating the performance benchmark based on the code profile and in machine-level timing data for the selected microprocessor. In this way, code security is achieved by fire-walling the object code from the second stage of the method.

Abstract: Methods and apparatuses are described for mutation testing of database functions. A computing device identifies database functions for testing from at least one database. The computing device generates, for each identified database function, mutated database functions by automatically applying mutations to the identified database function that change aspects of the identified database function. The computing device deploys the mutated database functions to the at least one database. The computing device determines line coverage attributes associated with each mutated database function. The computing device selects tests for execution against each mutated database function based upon the line coverage attributes associated with each mutated database function. The computing device executes the selected tests against each mutated database function using test automation applications to determine an outcome associated with each test.

Abstract: A system and method for adapting an errant automated decisioning workflow includes reconfiguring digital abuse or digital fraud logic parameters associated with automated decisioning routes of an automated decisioning workflow in response to identifying an anomalous drift or an anomalous shift in efficacy metrics of the automated decisioning workflow, wherein the automated decisioning workflow includes a plurality of distinct automated decisioning routes that, when applied in a digital threat evaluation of data associated with a target digital event, automatically compute a decision for disposing the target digital event based on a probability digital fraud; simulating, by computers, a performance of the automated decisioning routes in a reconfigured state based on inputs of historical digital event data; calculating simulation metrics based on simulation output data of the simulation; and promoting to an in-production state the automated decisioning workflow having the automated decisioning routes in the rec

Abstract: A method of building a device historian, across a supply chain of device manufactures and managers, by a plurality of device management services comprising an enrollment service, an update service, a policy service, and an analytics service, a transaction connector, a blockchain broker service participating as a node in a blockchain network, and transaction filters. The method comprises sending, by the plurality of device management services a transaction record over the transaction connector to the blockchain broker service, receiving, by the blockchain broker service, the transaction record, filtering, by the blockchain broker service, information in the transaction record based on the transaction filters, preparing, by the blockchain broker service, a versioned block based on the filtered information from the transaction record, and adding, by the blockchain broker service, the versioned block to the blockchain network.

Abstract: Techniques for a service provider network to allow users to quickly and easily establish a testing environment to test various virtual machine (VM) instance types for hosting their workloads. Rather than identifying and recommending optimized VM instance types for hosting workloads of users, the techniques allow for users to initially test the VM instance types and determine how well their workloads perform on the VM instance types. Users can quickly and easily (e.g., “one-click” input) request that a testing environment be established. The optimization service can then test one or more recommended VM instance types for the users' workloads in the testing environment. The optimization service can monitor the performance of the VM instance types while they host the “test workloads,” and provide the users with performance metrics to help them decide if they would like to migrate their workloads to the recommended VM instance types.

Abstract: A dynamic library replacement technique enables replacement of original functions or methods of application libraries based on analysis of traces captured by a client library of an investigative platform. Traces captured from the user application are analyzed to identify the original methods of the user application that may be replaced by the client library. The original methods may be identified based on estimated performance improvements determined from the analysis of the captured traces. The improved method replacements and estimated performance improvements may be graphically presented to a user via a user interface (UI) infrastructure of the investigative platform. Replacement of the improved methods may be defined in the dynamic configuration or interactively via the UI infrastructure and continued performance monitoring reported. The specific performance for any method may be monitored along with a fidelity of the monitored method.

Abstract: The present invention makes it possible to reduce the volume of communication data necessary for updating the configuration of a circuit unit of a reconfigurable circuit device. In an vehicle control system 10 including an FPGA 3, the FPGA 3 includes a circuit unit including a reconfigurable circuit and a circuit SRAM that stores configuration information of the circuit unit. A transfer check unit that acquires a difference command regarding a change part of a circuit element in the circuit unit, and a data conversion unit 4 that updates the configuration information based on the difference command are provided. Further, in the vehicle control system 10, a non-volatile memory 6 that stores the configuration information to be stored in the circuit SRAM is further provided. The data conversion unit 4 may update the configuration information stored in the non-volatile memory 6 based on the difference command acquired by the transfer check unit.

Abstract: Features of each ordered step of a recorded test script for an application under test (AUT) are generated. The ordered steps are segmentally organized over actions based on feature relatedness of the ordered steps. Each action includes a contiguous subset of the ordered steps. The actions are hierarchically organized within a tree based on an ordered feature relatedness of the actions. The tree has nodes respectively corresponding to the actions. The actions are abstractedly related to one another based on an unordered feature relatedness of the actions to generate abstracted actions that each generalize a subset of the actions. Abstracted action groups are generated based on the abstracted actions and the tree. Each abstracted action group includes abstracted actions mapping to corresponding nodes of the tree within a same branch. The ordered steps of the recorded test script are collapsed into a series of instantiations of the abstracted action groups.

Abstract: A directed graph for an application under test (AUT) hosted at a hosting computing device is generated based on test flows. Each test flow traverses GUI objects of the AUT via GUI events. Each GUI event is associated with a transition from a first GUI object of the AUT to a second GUI object of the AUT. The GUI event represents interaction with the GUI of the AUT at a client computing device and that resulted in the transition. The directed graph includes nodes that each correspond to a GUI object of the AUT and edges that each correspond to a GUI event.

Abstract: A system including a user interface, a memory, and a processor configured to perform operations stored in the memory is disclosed. The operations may include receiving an application specification including an application algorithm, and extracting from the application algorithm a first and a second node. The first node may include a first component of the application algorithm, and the second node may include a second component of the application algorithm that may be different from the first component. The operations may include analyzing execution dependency of the first node on the second node. The analyzing execution dependency may include analyzing computational requirements, bandwidth requirements, and input trigger requirements of the first node and the second node based on parallelism of available resources.

Abstract: Systems and methods for updating remote databases are provided. In certain embodiments, a method includes determining an installed version for a remote database stored on a vehicle computer. Further, the method includes identifying an incremental update for the remote database, wherein the incremental update contains differences between a desired version for the remote database and the installed version. Additionally, the method includes providing the incremental update to the vehicle computer. Also, the method includes updating the remote database with the incremental update.

Abstract: Defects are identified in a pre-production version of an application. Input used to test the pre-production version is derived from input received by a production version of the application. Input to the production version may be selectively filtered and/or amplified before being provided as test input to the pre-production version. In this way, the makeup and rate of the test input can be controlled while maintaining the character, pattern, and unpredictable nature of real-world input. Defects may be identified when the test input causes the pre-production version to crash, hang, write to an error log, or otherwise manifest or report a malfunction. In addition to identifying defects, filtered and amplified input may also be used to perform regression testing, load testing, performance testing, etc.

Abstract: An instrumentation trace capture technique enables software developers to monitor, diagnose and solve errors associated with application development and production. A client library of an investigative platform is loaded in a user application executing on a virtual machine instance of a virtualized computing environment. The client library interacts with an agent of the platform to instrument executable code of the user application and, to that end, loads a capture configuration that specifies, inter alia, methods and associated arguments, variables and data structures (values), to instrument. The client library inspects the executable code to determine portions of the code to instrument based on the capture configuration, which describes a degree of fidelity (e.g., a frequency) of the executable code and data to trace at runtime. Capture points of the runtime application are implemented as callbacks to the client library, which are registered with a runtime system executing the user application.