Abstract: A machine learning model is trained to translate source code from one or more programming languages into a common programming language. The machine learning model translates source code from the other languages into the common programming language. A language embedder generates a vector for each function in the source code, all of which is now in the common programming language. A user provides a text search query which is converted by a language embedder to a vector. Based on the vector of the text search query and the vectors for the source code, search results are generated and presented in a user interface. Additional machine learning models may be trained and used to measure function complexity, test coverage, documentation quantity and complexity, or any suitable combination thereof. These measures may be used to determine which search results to present, an order in which to present search results, or both.

Abstract: In an example embodiment, a novel “process assembly line” solution is provided that organizes software robots in a manner that, once configured, allows them to be duplicated and cloned into multiple scenarios, including in organizational structures where one software robot is triggered or called by another software robot. Instead of designing software robots with multiple functionalities in each to perform complex situations, the process assembly line can utilize software robots with single functions. This aids developers in building robust software robots and reduces potential errors.

Abstract: A system and method providing monitoring of services hosted by a hyperscaler environment. The method including receiving an indication of at least one metric related to a backup storage process for each of a plurality of hyperscaler hosted database service instances; determining at least one value for each of the plurality of database service instances; storing a record of the determined at least one value for each of the plurality of database service instances in a persistent data storage device that is distinct and separate from the database service instances; receiving a request from a third-party entity for the stored at least one value for at least one of the plurality of database service instances; and transmitting the requested one or more of the at least one value for the database service instances specified in the request.

Abstract: Techniques and solutions are described for retrieving metadata artefacts from a repository that includes multiple instances of a metadata artefact. The instances can have at least some different content. Metadata artefacts are associated with metadata describing group, searching, or selection criteria, such as one or more of a particular solution, tenant, layer, or version. A request for a metadata artefact can include at least one value for one or more of the criteria, which in turn can be used to identify one or more relevant metadata artefacts. Identifiers for, or content of, relevant metadata artefacts can be returned in response to the request. Fallback logic can be used to determine at least in part what metadata artefacts are relevant to a request, or how to return or process request results.

Abstract: Techniques and solutions are described for facilitating the reuse of text translations. For a first instance of text in a human language, a first logical pointer value is assigned to the first instance of the text, pointing to a target having at least a first translation for the text. A second instance of the text is received. If only the first instance is present, the first logical pointer value is assigned to the second instance. If a third instance of the text is present, associated with a second translation and a second logical pointer value, user or process input is received determining whether the first logical pointer value or the second logical pointer value is assigned to the second instance. Context information can be provided to a user to help determine whether the second instance should be associated with the first translation or the second translation.

Abstract: Systems, methods, and computer-readable media for controlling the execution of a deployed software program to a customer system are disclosed herein. A vendor may deploy a software program to the customer system. The software program may comprise an access key, the access key comprising a digital signature and access parameters. The digital signature may utilize a public key private key pair. The customer may run the software program by validating the access key on the customer system. Validating the access key may comprise verifying the digital signature and verifying the access parameters. Once the access key has been validated, the customer may execute the software program on the customer system.

Abstract: A method, a system, and a computer program product for placement or storage of data structures in memory/storage locations. A type of a data structure for storing data and a type of data access to the data structure are determined. The type of data access includes a first and a second type of data access. A frequency of each type of access to each type of data structure accessed by a query is determined. Using the determined frequency, a number of first type of data accesses to the data structure is compared to a number of second type of accesses to the data structure. The numbers of first and second types of data access are compared to a predetermined threshold percentage of a total number of data accesses to the data structure. Based on the comparisons, a physical memory location for storing data is determined.

Abstract: Provided is a system and method for generating an SQL operation from a natural language input using neural networks which works on data from a database that has not been seen before by the neural networks. In one example, the method may include receiving a natural language input, determining, via a first predictive module, a data structure of a SQL operation based on text included in the natural language input, filling in, via a second predictive module, one or more empty slots of the data structure of the SQL operation with text based on column names of a database and the text included in the natural language input, and storing the filled-in data structure of the SQL operation in a storage.

Abstract: A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database operation may be defined as a coroutine to at least enable the execution of the first instruction stream to be interleaved with an execution of a second instruction stream. In response to determining that data required to continue the execution of the first instruction stream is absent from a cache, the execution of the first instruction stream may be suspended and the second instruction stream may be executed instead. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: In an example embodiment, a solution is provided that causes a binary used by an in-memory database application to be deployed in a separate container. The container with the binary may be called a “sidecar” to the container with the in-memory database application. Both containers mount the same path in the hosts shared filesystem to expose the binary to the application. There is no permanent connection between the two containers, and thus the binary can be updated individually without inducing a downtime of the in-memory database application.

Abstract: Techniques for reducing CPU consumption in a federated search are disclosed. In some example embodiments, a computer-implemented method comprises determining an initial search scope by selecting a subset of searchable resources from a plurality of searchable resources based on interaction data of a user, with the initial search scope being defined by the selected subset of searchable resources, and the interaction data indicating online activity of the user directed towards past search results of past search queries submitted by the user. A federated search for a current search query is then performed using the initial search scope, with the federated search for the current search query being restricted to only the subset of searchable resources, and current search results for the current search query are generated based on the performing of the federated search.

Abstract: A method, a system, and a computer program product for generating a computational dependency directory and executing a query on a database using generated computational dependency directory. A data object in a plurality of data objects is stored in a database storage location. The data object includes a dependency parameter being indicative of the stored data object being dependent on at least another data object in the plurality of data objects. A query to access the stored data object in the plurality of data objects is received. A determination is made, using the dependency parameter, whether the stored data object is responsive to the received query. A query execution plan is generated based on the determining and the received query. The query is executed using the query execution plan.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: Methods, systems, and articles of manufacture, including computer program products, are provided for configuration monitoring. In some embodiments, there is provided a method that includes: sending a container image to a second cloud platform hosting a production system, wherein the container image includes configuration instructions to configure monitoring of an application at the production system hosted at the second cloud platform and at least one value to be monitored at the application at the production system hosted at the second cloud platform; receiving at least one message including the at least one value indicative of a current state of the application and/or the cloud platform; comparing the at least one value to at least one threshold; and in response to the at least one value exceeding the at least one threshold, sending an alert message.

Abstract: Systems, methods, and computer media for visualizing data are provided herein. The described examples allow one-dimensional data visualizations generated using visualization tools and backend components to be displayed in response to a request to view data that includes one or more sets of Cartesian columns. A data visualization request can specify data for inclusion in a data visualization and properties for the visualization, including transpose factors for data sources. The data sources having transpose factors can be cloned to represent respective combinations of the data source with each transpose factor, and then joined to other cloned or non-cloned data sources to generate the resulting one-dimensional visualization.

Abstract: In an example embodiment, machine learning is used to intelligently compress documents to reduce the overall footprint of storing large amounts of files for an organization. Specifically, a document is split into parts, with each part representing a grouping of text or an image. Optical character recognition is performed to identify the text in images. Machine learning techniques are then applied to a part of a document in order to determine how relevant the document is for the organization. The parts that are deemed to be not relevant may then be reduced in size, either by omitting them completely or by summarizing them. This allows for the compression to be tailored specifically to the organization, resulting in the ability to compress or eliminate parts of documents that other organizations might have found relevant (and thus would not have been compressed or eliminated through traditional means).

Abstract: Methods, systems, and computer-readable storage media for providing an insight provider including a logic component and a configuration component, the logic component including a domain-specific model, the configuration component including one or more parameter values for processing data using the domain-specific model, receiving a set of assets including data indicative of one or more assets, retrieving asset data associated with at least one asset of the first set of assets, the asset data including OT data and IT data, the OT data being provided from one or more networked devices, the IT data being provided from one or more enterprise systems, and processing the OT data and the IT data using the domain-specific model of the logic component to provide a result set, the result set including one or more of a second set of assets and enriched data.

Abstract: Data is received that defines a rule mining run including a scope of a search and at least one data source to be searched. In response, the at least one data source is polled to obtain rules responsive to the rule mining run. Each rule can specify one or more actions to take as part of a computer-implemented process when certain conditions are met. A list of rules (i.e., a proposed subset of the obtained rules) can then be generated using at least one machine learning model. The generated list of rule can then be displayed in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Abstract: Systems, methods, and computer-readable media are provided for determining a connection degree between users. Upon receiving user data, a report line hierarchy tree is updated, the hierarchy tree including user reporting information and relationships within an organization received from user profile data. A report line feature code is determined for each user by a feature code generator based on the report line hierarchy tree and stored in a data store. A location hierarchy tree is generated based on physical location information from the user profile data. A location feature code is determined for each user based on the location hierarchy tree and is also stored in the data store. To determine a connection degree between one or more users the feature codes including either or both of the report line feature codes and the location feature codes of the users are retrieved from the data store and compared.

Abstract: Techniques and solutions are described for propagating extensions to data artifacts, such as data artifacts defining objects in a physical or virtual data model. One or more data artifacts are identified that are related to a first data artifact. One or more extension elements of the first data artifact are analyzed for propagation to at least one data artifact of the one or more data artifacts. Analyzing whether an extension element should be propagated can include analyzing a type of the extension element, a type of operation or context in which the extension element is used, or how the at least one data artifact refers to, uses, or incorporates the first data artifact, including particular elements thereof. The results of the analysis are compared with various rules. Extension elements are propagated automatically, manually upon user approval (e.g., propagation recommendations are provided), or in a semi-automated manner.