Abstract: Technologies are described for facilitating database system recovery in a distributed database environment having a master node and at least one slave node. The master node maintains an in-memory reference that includes transaction identifiers and their corresponding commit identifiers. When a slave node requests that a commit identifier be assigned to a transaction, the transaction and commit identifiers for the transaction are added to the in-memory reference. The commit identifier is sent by the master node to the slave node. The slave node writes a log entry to a commit log that includes the transaction identifier and the assigned commit identifier. If the database system is interrupted before the slave node writes the commit log entry, the slave node can request the commit identifier for the transaction from the master node, which retrieves the identifier from the in-memory reference.

Abstract: Techniques are described for predicting test scenarios and generating test case documents and/or automation scripts using machine-learning algorithms. For example, input may be received representing a web page, and an HTML Document Object Model (DOM) of the web page may be analyzed. From the DOM, a plurality of HTML elements may be extracted and processed by a machine-learning algorithm. Based on the processed plurality of HTML elements, a plurality of predictions for test case scenarios may be generated, and converted into a set of human-readable instructions, such as a test case document, and/or a set of machine-readable instructions, such as an automation script. In some instances, a user selection of at least one predicted test scenario from a displayed list of one or more predicted test scenarios is received and corresponding human-readable instructions and/or machine-readable instructions are generated for the selected scenario(s).

Abstract: A system and method include detection of a set of sequential interactions with a user interface, storage of a recording comprising data associated with a set of sequential calls to a user interface entry point application programming interface of a server application caused by the set of sequential user interface interactions, association of the recording with an incident identifier, reception of a request to analyze an incident associated with the incident identifier, and, in response to the request, initiation of playback of the recording, wherein playback of the recording comprises reading of the data of the recording and, based on the read data, issuing the set of sequential calls to the user interface entry point application programming interface of the server application.

Abstract: Structure data is received from a database. The structured data may comprise data values and specifying relationships among the data values. A method is provided to include receiving selections of operations to be performed on the structured data and an order of the operations. The operations may include at least one permutation operation. The method may include determining a graphically displayable data format based on the selections of operations. The method may include representing the structured data and the relationships among the data values in the graphically displayable data format. The method may comprise performing operations according to the selections, including, permuting entries of the graphically displayable data format. The permuting may comprise bringing the entries of the graphically displayable data format into a logical order while maintaining the relationships. The method may also include displaying the entries for analysis after performing the operations.

Abstract: Some embodiments provide a program that determines a version of a first set of application resources. The program further determines whether a version of a second set of application resources is different and compatible with the version of the first set of application resources. Upon determining that the version of the second set of application resources is different and compatible with the version of the first set of application resources, the program also uses the second set of application resources to generate visualizations of data while downloading the first set of application resources for later use. Upon determining that the version of the second set of application resources is different and not compatible with the version of the second set of application resources, the program further downloads the first set of application resources and uses the first set of application resources to generate visualizations of data.

Abstract: Methods, systems, and computer-readable storage media for processing, through an encoder of an attention-reconstruction-based summarization (ARS) platform, the primary document to provide a contextual vector, identifying, using reconstruction regularizers of the ARS platform, information that is absent from the one or more linking documents, and is present in the primary document at least partially based on the contextual vector, for each word of the primary document, providing, using an attention mechanism of the ARS platform, a word salience score at least partially based on the information that is absent from the one or more linking documents, for each sentence in the primary document, determining a sentence salience score based on word salience scores of words within the sentence, ranking sentences of the primary document based on sentence salience scores, and selecting two or more sentences of the primary document based on ranking to provide a summary of the primary document.

Abstract: A client comprising a web browser is provided. The client is configured to: run an application in the web browser, the application comprising a sensor including sensor JavaScript code, wherein running the application comprises executing the sensor JavaScript code as the first JavaScript code in the web browser to activate the sensor; and wherein the sensor is configured to: gather data with respect to the application at runtime; and check predetermined application-specific rules against the gathered data for detecting client-side attacks at runtime.

Abstract: An adapter framework is provided for consuming resources provided by a database service by client applications. A location of an interface of the database service is received. Static metadata of a client application is received from the client application. Mapping of field names defined at the database service to field names defined in the client application is received at the framework. Metadata for a service interface is created at the adapter framework based on the received static metadata and dynamic metadata for dynamic fields from the database service. The mapping of field names is appended with mappings for the dynamic fields. At a runtime processor, a type of a data request from the client to the database service is determined. The request is processed and a response from the database service is generated by the adapter framework and provided to the client application in an expected format.

Abstract: Various examples are directed to systems and methods for securing a web browser. The web browser may parse web content received from a server and identify a script associated with the web content. The web browser may generate script fingerprint data for the script. The script fingerprint data may comprise script code data describing script code for the script and script syntax data describing the script. The web browser may determine that the script fingerprint data is not described by local known script data and may send an anomalous script report to the server, where the anomalous script report comprising the script fingerprint data. The web browser may also update the local known script data to describe the script fingerprint data.

Abstract: A retention service registers a target system as a consumer service. A cloud platform provides services to each of multiple consumer service. Retention rule information about the target system is received and reflects a data retention requirement. A rule is created that corresponds to the data retention requirement. A configuration is defined that specifies recurring future invocations of the rule. The rule is invoked per the configuration and a query is sent to the target system, the query configured to extract data. Extracted data is received and the rule is applied thereto. An action specified by the rule is taken with regard to the data.

Abstract: A computer-implemented method, system, and computer program product are described for initiating and displaying, at a user interface, an editor adapted to generate a plurality of configuration models, receiving a selection of at least one country from a plurality of countries. The method can include retrieving a data model and reference data associated with the at least one country, populate a plurality of attributes from the data model in the user interface and populating a plurality of selectable input mappings in the user interface. The method may also include populating a plurality of selectable output mappings in the user interface and generating at least one configuration model, in response to receiving at least one selection for the input mappings and at least one selection for the output mappings.

Abstract: Disclosed herein are system, method, and computer program product embodiments for interactive exploration of graph data. An embodiment operates by compiling a data query in any database-readable language based upon an input parameter. A data query of a graph data set is then conducted but is halted when a breakpoint generated from the input parameter is reached. Halting the data query includes partitioning a data subset from the graph data set. The data subsets is then displayed.

Abstract: Systems and methods are provided for retrieving a set of code changes to source code from a source code repository, analyzing the set of code changes to generate a vector representation of each code change of the set of code changes, analyzing the vector representation of each code change of the set of code changes using a trained security-relevant code detection machine learning model, receiving a prediction from the security-relevant code detection machine learning model representing a probability that each code change of the set of code changes contains security-relevant changes, analyzing the prediction to determine whether the prediction is below or above a predetermined threshold, and generating results based on determining whether the prediction is below or above a predetermined threshold.

Abstract: Embodiments implement leakage-free order-preserving encryption by assigning a distinct ciphertext for each plaintext, including repeated plaintext whose ciphertext is randomly inserted. In order to conceal insertion order, the randomized ciphertexts are compressed to minimal ciphertext space. A uniform distribution is achieved by rotating about a modulus on the ciphertexts rather than the plaintexts. The resulting ciphertext distribution has no leakage from the ciphertexts—even if an adversary has perfect background knowledge on the distribution of plaintexts. The encryption may be further secured even against passive query monitoring attacks by hiding the access pattern using ?, ?-differential privacy, such that the adversary observing a sequence of queries will not learn the frequency of plaintext. The leakage-free order-preserving encryption may be converted into an adjustable encryption scheme to allow querying (e.g., on a remote server).

Abstract: In a process of transfer of production control in proximity to production site for enabling decentralized manufacturing, production control data and routing data are retrieved from a centralized system. The retrieved production control data and the routing data are stored within a connector installed at a proximity to a plant floor. An operation associated with the production control data of a purchase order is matched with the resource published in the connector. Upon determining the match between the operation and the resource, the resource is dynamically allocated to perform the operation. The control of manufacturing process of the plant floor is provided to the connector to realize de-centralized manufacturing.

Abstract: A calculation engine of a database management system is described. In some implementations, the calculation engine receives a calculation scenario including a plurality of calculation views comprising one or more relational operations. The calculation engine determines whether a first calculation view includes a second calculation view configured as an operand of one of the relational operations of the first calculation view, and also determines whether the second calculation view comprises a non-relational operation. The calculation engine further converts the plurality of calculation views into a calculation plan via merging the first calculation view with the second calculation view when the first calculation view is determined to comprise the second calculation view as an operand, and replacing the second calculation view with a view search operation when the second calculation view is determined to comprise the non-relational operation.

Abstract: In one embodiment, the present disclosure pertains to testing. In one embodiment, software tests are performed on a first software server. Tests may be repeated a plurality of times to check for consistent failures or passes. Test results are sent to a second software server. The test results are stored in one or more databases on the second software server, where particular test results are associated with one or more fields specifying whether the test was passed and whether the test was failed. Tests that were both passed and failed may be deemed “flaky” tests. The second software server may generate a query to retrieve test results from the database that both passed and failed at least one test (flaky tests). Flaky tests may be quickly retrieved and processed.

Abstract: A significant correlation framework is provided herein for translating input commands to intents. The input commands may be natural language commands, received from a variety of input channels, which may be translated to intents or other runtime-bindable execution objects. The significant correlation framework may use interpreter nodes for translating the input commands by calculating the strength of correlation between an input command and an intent. The significant correlation framework may analyze the sequence of intents or the timing of translated intents to enhance the accuracy of the translation. The significant correlation framework may maintain a history of command translations, and may compare current translations against the history to improve accuracy of the translations. The significant correlation framework may switch between a depth-first mapping method and a breadth-first mapping method. Depth-first mapping may translate commands through a single interpreter node.

Abstract: A method for data model clustering is provided herein. A first representation of a data model may be received. Edge betweenness values may be determined for respective nodes in the first representation. At least one node in the first representation may be identified as a linking node based on the respective edge betweenness values. One or more linking nodes may be removed from the first representation, thereby forming at least a first cluster and a second cluster. Degrees for the respective remaining nodes may be calculated. Respective hub nodes may be identified for the respective clusters based on the respective degrees in the clusters. Respective descriptions may be generated for the respective clusters based on the respective hub nodes. A clustered representation of the first representation may be stored with the clusters and their respective descriptions.

Abstract: A metastructure for representing and manipulating or analyzing a data model is provided herein. A source representation of the first data model may be received. The source representation may include a representation of one or more structural components of the first data model, respectively having identifiers and types. One or more instances of a metastructure schema object datatype may be generated based on the one or more structural components of the source representation. Generating a given instance of the metastructure schema object datatype for a given structural component may include assigning a first identifier of the given structural component to the first data member of the given instance, determining a first type associated with the given structural component, and assigning the first type to the second data member of the given instance. The one or more instances of the metastructure schema object datatype may be stored in association.