Abstract: Systems, methods, and computer media for blockchain-based communication between applications are provided herein. Using a blockchain-based multi-application communication platform, different applications can create and interact with trusted records. A trusted record represents something quantified and/or tracked through an application. Trusted records are stored in a blockchain. Trusted records can be created by one application and accessed by other applications through the platform. Interactions of the different applications with a trusted record are also stored in the blockchain. The immutability of information stored in the blockchain ensures that the trusted records can in fact be trusted, ensures that interactions with trusted records are memorialized, and removes uncertainty as to which application's records are correct.

Abstract: The present disclosure involves systems, software, and computer implemented methods for generating a unified semantic model identifying a user's intentions or goals within operating the system. By determining the intent and desires of the user, tasks and queries associated with or requested by the user can be more effectively optimized, automated, or otherwise improved. In some computing environments, multiple users access a database which includes a collection of software objects. The objects within the database can sometimes form a hierarchy, with a parent-child relationship among them. Traditionally, a developer creating the database and the objects within can only determine a user's intent based on the actions taken by the user within the database. The present solution provides the developer with a higher level model representing different users' intents based on observed data from a number of sources in addition to the user's interaction with the database.

Abstract: Techniques and solutions are provided for improving query performance of queries that can dynamically switch between accessing different data sources for a particular operation. The disclosure provides an object type, which can be referred to as a configuration object, that specifies which of multiple data sources should be used in query execution at a particular point in time. Values that specify a data source can be included as data in an instance of the object type, such as values in a relational database table that implements the configuration object. A data source to be used with a query can be changed dynamically by updating contents of the table. During query optimization, a query optimizer can recognize that the configuration object is of a particular type that causes the query optimizer to access contents of the configuration object. The contents can be used to prune portions of a query plan.

Abstract: A digital assistant can provide support for automated testing of applications. A natural language interface can be provided by which a testing user can specify a request for one or more testing actions. A natural language processing model can recognize intents in the request, and the intents can be used to execute executable code to perform the requested testing actions. Multiple actions per request can be supported. An object repository can be leveraged to determine user interface control identifiers, and a test data container can store values for use during testing. Testing functionality can thus be provided to a wider base of testing users. A real time, scriptless approach can conserve computing resources.

Abstract: Techniques and solutions are provided for improving query performance using inverse functions. Often a function is used to perform operations such as data type conversions. The use of these functions can be resource intensive, such as if a conversion needs to be performed for all rows of a particular relational database table. The present disclosure allows for the registration of inverse functions that can be used, or at least be considered for use, in place of a function. A given inverse function can be associated with its function using techniques such as maintaining mapping information or using a particular naming convention. A particular syntax is provided for designating and creating an inverse function.

Abstract: Techniques and solutions are described that can be used to determine data subsets of a data set that may be responsive to a query. In one aspect, imprints are created for the data subsets, where an imprint indicates whether, for a plurality of bins, a data subset contains values within respective bins. The bins are defined at least in part using data for a set of queries. In another aspect, at least one bin of a plurality of bins is designated to be associated with values of the data set satisfying a threshold frequency. In a further aspect, imprints are created for a plurality of bins, where an imprint indicates whether the plurality of data subsets comprise a value for a given bin. A query imprint can be compared with the data subset imprints or bin imprints to determine data subsets that may be responsive to an associated query.

Abstract: A method may include receiving a workspace definition defining a graph workspace for a heterogeneous graph having a plurality of vertex tables and/or edge tables. Upon validating the workspace definition, the graph workspace for the heterogeneous graph may be created in accordance with the workspace definition. The graph workspace may include a label for each table of the plurality of vertex tables and/or edge tables comprising the heterogeneous graph. Each vertex and edge of the heterogeneous graph may be uniquely identified based on a label of a corresponding table and one or more key attributes. A graph processing algorithm operating on the heterogeneous graph may be executed based on the graph workspace. Related systems and computer program products are also provided.

Abstract: Example embodiments for evaluating programmable conditions applicable to an operation are described. In an example embodiment, a request to evaluate one or more programmable conditions applicable to an operation is received. The request includes data associated with the operation. One or more objects representing the one or more programmable conditions are retrieved from a database. The one or more objects include executable code for determining compliance of the operation with the one or more programmable conditions. At least a portion of the executable code is executed based on the data associated with the operation. An output of the executable code is returned to a computing system issuing the request. The output includes an indication as to whether the operation complies with the one or more programmable conditions.

Abstract: Techniques for implementing enterprise search using database views are disclosed. In some example embodiments, a computer-implemented method comprises: receiving database queries; generating, for each database query, a corresponding database view comprising a result set arranged in one or more fields of a table; storing the corresponding database views of the database queries; generating a corresponding search configuration for each one of the stored database views, the corresponding search configuration indicating the field(s) of the table of the stored database view; storing the corresponding search configurations for the stored database views; receiving an enterprise search query comprising one or more terms entered via a full-text search field; generating search results for the enterprise search query based on the term(s) using the stored search configurations to access data in the field(s) of the tables of the stored database views; and causing the generated search results to be displayed.

Abstract: Embodiments store attributes extracted from incoming media data (e.g., image, audio, video), in a media store residing in a data lake together with other, non-media attributes. In response to incoming media data (e.g., an image), an engine references an unpopulated media attribute schema resulting from processing a trained deep learning model (e.g., a Convolutional Neural Network—CNN model). The engine applies the deep learning model to extract from the incoming media data, a media attribute (e.g., a cloudy spot dimension) comprising a prediction value and a confidence. The engine populates the media attribute schema with the attribute (value; confidence) and an identifier, and stores the populated media attribute schema in the data lake. The data lake also includes a non-media attribute (e.g., patient info) sharing the identifier. Now, the data lake may be queried for both the non-media (patient info) attribute and the media (image) attribute extracted by the model.

Abstract: A method may include determining, based at least on an image of a document, a plurality of text bounding boxes enclosing lines of text present in the document. A machine learning model may be trained to determine, based at least on the coordinates defining the text bounding boxes, the coordinates of a document bounding box enclosing the text bounding boxes. The document bounding box may encapsulate the visual aberrations that are present in the image of the document. As such, one or more transformations may be determined based on the coordinates of the document bounding box. The image of the document may be deskewed by applying the transformations. One or more downstream tasks may be performed based on the deskewed image of the document. Related methods and articles of manufacture are also disclosed.

Abstract: In some example embodiments, there is provided a method that includes receiving a query for query plan generation and query plan optimization; detecting whether the query plan includes a restart pipeline, the restart pipeline including one or more first operators that cause a query plan restart; detecting whether the query plan includes a result pipeline, the result pipeline including one or more second operators that provide result streaming; determining whether there is a dependency between execution of the restart pipeline and execution of the result pipeline; in response to determining there is no dependency, reordering the restart pipeline in the query plan such that the restart pipeline will be executed before the result pipeline in order to enable result streaming optimization; and providing the reordered query plan for execution. Related systems and computer program products are also provided.

Abstract: In an example embodiment, three roles are defined for each of the following: resource discovery: provider, aggregator, and consumer. The provider is the one whose resource information will be shared. Rather than the provider needing to implement the complicated API, however, an aggregator may provide that role. The aggregator defines the API and is able to gather resource information from potentially multiple providers (and also, in some embodiments, other aggregators). The consumer then accesses the aggregator to obtain resource information rather than directly accessing the provider.

Abstract: The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes receiving, from a requesting application in a landscape that includes a set of multiple applications, a data subject information request for a data subject. A set of target applications is determined from the set of multiple applications. The data subject information request is provided to each target application in the set of target applications. A data subject information response is received from each of the target applications. Each data subject information response includes application data for the data subject that was retrieved by a respective target application in response to the data subject information request. The received data subject information responses are aggregated to generate an aggregated data subject information response.

Abstract: Aspects of the current subject matter are directed to performing privacy-preserving analytics over sensitive data without sharing plaintext data and without requiring a trusted third party. Implementations provide for utilizing a trusted execution environment within a server to compute the privacy-preserving result. Data owners via user devices send their encrypted data directly to an enclave managed by a trusted execution environment, without the server and the cloud service provider for the server seeing the plaintext data. The enclave computes the analytics directly on the data and releases the privacy-preserving result that can be ensured by code analysis and remote attestation from all parties.

Abstract: A computer implement method can create an entity close scheme including a plurality of nodes and edges connecting the plurality of nodes. The nodes represent task objects and the edges define predecessor-successor relationship between pairs of nodes. The method can execute the task objects and monitor status of the task objects. After flagging the status of a completed task object represented by a selected node to be invalid based on evaluation of results of the completed task object, the method can determine downstream nodes of the selected node, then identify contingent downstream nodes among the downstream nodes of the selected node, and flag the status of task objects represented by the contingent downstream nodes to be invalid upon completion of the task objects represented by the contingent downstream nodes.

Abstract: In an example embodiment, machine learning techniques are utilized to create virtual tables that connect to actual tables in a user's own system. The virtual table predicts how the user's data can be used to populate fields in newer versions of software that the user already runs, even when those fields are not present in the version that the user already runs. These tables may then be used in a specialized tool, which displays in one area of the display a screen of the version of the software that the user is currently running (“the existing version”) and displays in another area of the display a screen of the version of the software that the user is comparing to the existing version. Both display areas display the same screen, as rendered by their respective different versions of the software, using the same underlying base data.

Abstract: A method includes receiving a message query from an entity identifier participating in a social network. The message query specifies one or more entities, one or more requirements, and one or more constraints. A set of message query parameters is generated based on the message query. A set of queries for a semantic graph of the social network is generated based on the set of message query parameters. The set of queries is applied to the semantic graph to obtain a set of query results. A message context of the entity identifier is determined based on the set of query results and the set of message query parameters. A set of messages from a message repository is determined based on the message context. The set of messages can be presented on a client computer associated with the entity identifier.

Abstract: A computer-implemented method can receive a software update for a software application deployable on a target system and perform an automatic performance test of the software application incorporating the software update on the target system. The automatic performance test can be integrated in a continuous integration and continuous delivery (CI/CD) pipeline. The method can collect a plurality of performance metrics measured when performing the automatic performance test and determine a performance score based on the plurality of performance metrics. Responsive to detecting the performance score is below a predefined performance threshold, the method can cause the CI/CD pipeline to reject the software update to the software application.

Abstract: A first forwarding VM may execute in a first availability zone and have a first IP address. Similarly, a second forwarding VM may execute in a second availability zone and have a second IP address. The first and second IP addresses may be recorded with a cloud DNS web service of a cloud provider such that both receive requests from applications directed to a particular DNS name acting as a single endpoint. A service cluster may include a master VM node and a standby VM node. An IPtable in each forwarding VM may forward a request having a port value to a cluster port value associated with the master VM node. Upon a failure of the master VM node, the current standby VM node may be promoted to execute in master mode and the IPtables may be updated to now forward requests having the port value to a cluster port value associated with the newly promoted master VM node (which was previously the standby VM node).