Abstract: A deep learning-based Java program internal annotation generation method and system is provided. The method includes acquiring items with a Stars number ranked in the top, and extracting corresponding internal annotations and method statement lists; obtaining an <annotation, target code> pair; selecting an annotation in a Verb-dobj form; obtaining a code context associated with a target code segment; preprocessing the annotation, the target code, and the context to obtain a triplet dataset; randomly dividing the constructed dataset into a training set, a validation set, and a test set, and constructing an encoder-decoder network at the same time; enabling the training set in division to be used for model training, performing evaluation on the validation set to obtain a model with the best effect on the validation set as a target model; and predicting data in the test set with the obtained target model to generate a predicted annotation.

Abstract: An application platform system and method. A data synchronization instance manages a reference state object for a data synchronization system (DSS) account. A first local state object is stored at a first application system. The first application system receives update notifications provided by the DSS. A second local state object is stored at a second application system. The second application system receives update notifications provided by the DSS. An application instruction of the first application system is transformed into a state update, and the first local state object is modified to include the state update. The state update is provided to the DSS via a local update notification. The reference state object is modified to include the state update. The state update is provided to the second application system via a reference update notification. The second local state object is modified to include the state update.

Abstract: Embodiments are generally directed apparatuses, methods, techniques and so forth determine an access level of operation based on an indication received via one or more network links from a pod management controller, and enable or disable a firmware update capability for a firmware device based on the access level of operation, the firmware update capability to change firmware for the firmware device. Embodiments may also include determining one or more configuration settings of a plurality of configuration settings to enable for configuration based on the access level of operation, and enable configuration of the one or more configuration settings.

Abstract: A system can determine to uninstall a patch that is installed on a computer, wherein an image of an operating system of the computer and a package that was used to install the patch are cryptographically signed. The system can further identify a first stored location of the package, and a second stored location of the image of the operating system. The system can further extract a file manifest from the package at the first stored location. The system can further extract versions of files identified on the file manifest from the image of the operating system at the second stored location, resulting in extracted versions of files. The system can further store the extracted versions of files to a temporary storage location. The system can further move the extracted versions of files in the temporary storage location to respective original running locations of the versions of files.

Abstract: A method for instrumenting an update to a software application may include determining, based on a source code file affected by the update to the software application, a first method affected by the update to the software application. A second method called by the first method and a third method called by the second method may also be identified as being affected by the update to the software application. A user interface file that includes a call to the first method, the second method, and/or the third method may be identified. The functional impact of the update may be determined by identifying one or more functional flows that match the user interface file. A recommendation identifying the one or more matching functional flows as candidates for testing may be generated. Related systems and computer program products are also provided.

Abstract: In a relay apparatus, if partial data that is a portion of update data that is used to update a control program is input to a second input/output unit, a control unit stores the partial data in a storage unit. If partial data is input to a first input/output unit while partial data is being repeatedly input to the second input/output unit, the control unit stops storing the partial data input to the second input/output unit and stores the partial data input to the first input/output unit in the storage unit.

Abstract: A computing device is disclosed herein. The computing device includes a memory that stores processor executable instructions for an application development platform and a context-aware undo-redo service of the application development platform. The computing device includes a processor that executes the processor executable instructions to cause the computing device to receive a first invocation of an undo operation with respect to environment variables on screens. The computing device further navigates, according to an active context, to a configuration screen of the screens to make the configuration screen visible in response to the first invocation. The configuration screen shows a portion of the environment variables. The computing device also receives a second invocation of the undo operation and executes the undo operation in response to the second invocation to reverse changes to the portion of the environment variables shown by the configuration screen while the configuration screen is visible.

Abstract: Disclosed herein are methods, systems, and computer-readable media for generating computer code based on natural language input. In an embodiment, a method may comprise one or more of: receiving a docstring representing natural language text specifying a digital programming result; generating, using a trained machine learning model, and based on the docstring, a computer code sample configured to produce respective candidate results; causing the computer code sample to be executed; identifying, based on the executing, a computer code sample configured to produce a particular candidate result associated with the digital programming result; performing at least one of outputting, via a user interface, the identified computer code sample, compiling the identified computer code sample, transmitting the identified computer code sample to a recipient device, storing the identified computer code sample, and/or re-executing the identified computer code sample.

Abstract: A method of adaptably allowing an upgrade to firmware or a configuration of target endpoint hardware to be at least one of replaced or modified by way of instructions generated by a patch generator and executed by target endpoint hardware to generate an upgrade file, install the upgrade file, and audit the installation of the upgrade file is disclosed.

Abstract: A system for reference-aware application recreation in a container deployment environment is presented. The system includes a reference detection module configured to detect and store one or more reference paths corresponding to each resource type of a plurality of resources in the container deployment environment; a resource ordering module configured to generate a recreation sequence by ordering the plurality of resources based on corresponding references at the reference paths, such that a referenced resource is recreated before the referring resource; and an application recreation module configured to recreate an application based on the recreation sequence. A related method is also presented.

Abstract: Obtaining a configuration hook. Obtaining a base configuration of a remote system using the configuration hook. Obtaining a system-specific model associated with the configuration hook and the remote system. Obtaining one or more pre-built test accelerators. Obtaining a deep machine learning model. Generating, based on the base configuration, the system-specific model, the one or more pre-built test accelerators and the deep machine learning model, a custom configuration model. Generating a plurality of user journeys to be autonomously tested. Generating, based on the custom configuration model and the plurality of user journeys to be autonomously tested, a plurality of autonomous test scripts. Autonomously pre-configuring at run-time the plurality of autonomous test scripts. Autonomously executing the plurality of autonomous test scripts. Generating, based on the autonomously executed plurality of autonomous test scripts, one or more autonomous test reports.

Abstract: In general, techniques are described by which to perform memory efficient patching for computing devices. A server computing device comprising a memory and a processor may be configured to perform the techniques. The memory may store first assets that form an unpatched application and second assets that form a patched application. The processor may virtualize the first assets to obtain a single first virtual asset and obtain a single second virtual asset that represents the second assets. The processor may obtain, based on differences between the single first virtual asset and the single second virtual asset, a patch identifying how to update the single first virtual asset to obtain the single second virtual asset. The processor may next segment the patch into a plurality of segments and output to a user computing device a single segment from the plurality of segments for individual application by the user computing device.

Abstract: Systems and methods are described that use software diversification techniques to improve the security of mobile applications. Embodiments of the disclosed systems and methods may, among other things, facilitate secure application distribution through deployment of diverse of applications in an application distribution channel. Software diversification consistent with certain disclosed embodiments may mitigate large-scale automated circumvention of security protections by presenting attacking malware moving and/or otherwise unpredictable diverse targets.

Abstract: The subject technology provides receiving a neural network (NN) model to be executed on a target platform, the NN model including multiple layers that include operations and some of the operations being executable on multiple processors of the target platform. The subject technology further sorts the operations from the multiple layers in a particular order based at least in part on grouping the operations that are executable by a particular processor of the multiple processors. The subject technology determines, based at least in part on a cost of transferring the operations between the multiple processors, an assignment of one of the multiple processors for each of the sorted operations of each of the layers in a manner that minimizes a total cost of executing the operations. Further, for each layer of the NN model, the subject technology includes an annotation to indicate the processor assigned for each of the operations.

Abstract: A system and method for detecting code initialization actions is utilized for performing static analysis of an application code including an external initialization component. The method includes receiving an application code including an external initialization code component, the application code deployed in a cloud computing environment; detecting in the application code an anchor point, the anchor point including a call to another code object; inserting a hook into the application code based on a location of the anchor point in the application code; and receiving a result from the hook in response to executing the application code.

Abstract: A data exchange system comprises an electronic smoking device that includes identifying data and a database configured to i) receive the identifying data from the electronic smoking device, ii) receive user data for a user of the electronic smoking device from a processor, iii) associate the identifying data with user data to generate a user record, and iv) store the user record.

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: A computer that dynamically maps traffic to different versions of software is described. During operation, the computer may receive first traffic from a first tenant and second traffic from a second tenant, where the first traffic and the second traffic are addressed to a common computing environment that supports multiple, different tenants. Then, the computer may identify the first tenant based at least in part on first information included in the first traffic, and may identify the second tenant based at least in part on second information included in the second traffic. Moreover, the computer may dynamically map the first traffic to a first version of software and the second traffic to a second version of the software, where the dynamic mapping occurs at runtime. Note that the computer may concurrently execute the first version of the software and the second version of the software.

Abstract: A testing system, tool and method for determining anonymization process quality are disclosed. The testing tool includes a processor, a communications module coupled to the processor, and a memory coupled to the processor. The memory stores computer executable instructions that when executed by the processor cause the processor to obtain a first dataset comprising data to be anonymized. The processor obtains a second dataset comprising data resulting from the first dataset being subjected to an anonymization process by a testing platform to anonymize a portion of the first dataset and generates a visual representation of the first dataset. The processor generates a second visual representation of the second dataset, the second visual representation reflecting at least in part a transformation from the first dataset to the second dataset. The processor generates an output including the first and second visual representations, the output being illustrative of the transformation.

Abstract: According to examples, an apparatus may include a processor that may delete portions of firmware instructions responsive to an indication that the portions should be disabled. To facilitate the foregoing, the firmware instructions may be deployed in a segmented architecture stored in respective regions of a storage device. The regions may include a metadata region, a main region, and excludable regions. The metadata region may store metadata that describes the structure of the firmware instructions and/or the various other regions. The main region may store core firmware instructions that may not be deleted. Each excludable region may store respective excludable firmware instructions. Each excludable firmware instructions may be associated with a flag that indicates whether or not the instructions should be disabled. If so, the corresponding excludable region in the storage device is identified and the contents may be removed, permanently disabling the excludable firmware instructions that were stored there.