Abstract: Techniques and solutions are described for detecting and correcting errors in software, such as in source code, using machine learning. A machine learning algorithm can be trained using source code, source code corrections, and extracted code features to provide a trained classifier. Test data, such as code to be scanned for errors or code known to have an error, can be submitted to the trained classifier. The classifier can generate a code correction or corrected code. Code corrections can be applied to the source code to provide corrected code.

Abstract: Methods and system are disclosed that generate adapters via a framework. In one aspect, dependencies between components may be defined via a drag-and-drop action on a user interface provided via an adapter configuration user interface component. Adapter configuration files may be generated by an adapter configuration component, such that the adapter configuration files may include information associated with the dependencies. At runtime, a dependency analyzer component may resolve the dependencies based on definitions associated with the dependencies. In an embodiment, upon resolving the dependencies, adapters may be generated at the framework.

Abstract: Techniques and solutions are described for facilitating the installation of software application extensions in a multi-tenant environment. A package for an extension may include code for a plurality of objects of the extension. Extension objects can be generated or non-generated. Generated objects can be user modifiable or not user modifiable. A software-implemented classification assistant can examine properties of the objects and classify them for deployment to a shared container or prompt a user to select whether an object should be deployed to the shared container or to a tenant-specific container. Properties of objects in the shared container may be set by the classification assistant such they are not modifiable by tenants.

Abstract: Technologies are described for restarting an application while maintaining data in memory (e.g., using shared memory). For example, shared memory can be associated with an application. The shared memory can also be associated with a holder process to maintain the shared memory from the time the application stops to the time the application starts again. When the application starts, the shared memory can be associated with the started application. In addition, restart of in-memory databases can be provided using shared memory. For example, in-memory data can be maintained when a database process or database management system stops and starts (e.g., during a restart).

Abstract: String comparison, including comparing strings with a rule, can be time consuming, and strings may not be suitable for analysis using machine learning algorithms. The present disclosure provides positionally-encoded representations of strings, such as binary matrices or arrays, that provide an encoded representation of the string. The encoding, and decoding, can be facilitated by an encoding schema, such as an encoding schema stored in the memory of a computer device. The encoding schema associates particular characters with particular positions in an array. The positionally-encoded string representations can be used for security applications, such as to determine whether an authorization token that includes at least one string complies with an authorization rule. The authorization rule can be specified as a positionally-encoded representation that defines a set of strings that comply with the rule.

Abstract: Disclosed herein are system, method, and computer program product embodiments for error root cause detection. An embodiment operates by a computer implemented method that includes receiving, by at least one processor, a request to determine a root cause of an error associated with a code and executing a first execution path and a second execution path, where the first and second execution paths correspond to the code. The method further includes determining whether a difference between first data generated by the execution of the first execution path and second data generated by the execution of the second execution path affects the error associated with the code. The method also includes identifying a code component that contributed to the difference between the first data and the second data, if the difference between the first data and the second data affects the error associated with the code.

Abstract: In one embodiment, a method stores a mapping table that includes a zero data identifier corresponding to a zero data record in the second database table. The method receives a query for data in a cube data structure. A first join between the first database table and the mapping table and a second join between the second database table and the mapping table are performed to generate a combined table for the cube data structure. The combined table includes a combined record that includes information from a first record from the first database table and includes the zero data identifier with information from the zero data record in the second database table when the first record for an entity in the first database table does not include a corresponding second record for the entity in the second database table.

Abstract: Implementations of the present disclosure include methods, systems, and computer-readable storage mediums for performing actions during simulation of an application interacting with a hybrid memory system, actions including providing a first range of virtual addresses corresponding to a first type of memory in the hybrid memory system, and a second range of virtual addresses corresponding to a second type of memory in the hybrid memory system, receiving a data packet that is to be stored in the hybrid memory system, determining a virtual address assigned to the data packet, the virtual address being provided in cache block metadata associated with the data packet, and storing the data packet in one of the first type of memory and the second type of memory in the hybrid memory system based on the virtual address, the first range of virtual addresses, and the second range of virtual addresses.

Abstract: Embodiments include an improved database logging system where transactions are allocated to multiple different partitions of a database log file and log records for transactions are written to different partitions of a database log. Each partition can store log records for a separate transaction in a separate log cache memory. Writing log records to a page of the database log can be prevented until previous log records modifying that same page have been written to disk. A sequential timestamp that is unique across the plurality of partitions may be assigned to the log records for this purpose, and a log record containing a modification to a page can be flushed after previous modifications to the page have been written to disk. Restore operations can then be performed by copying the log records of the multiple partitions into a priority data structure and ordered into a merged list based on timestamp.

Abstract: A configuration is received for an agent associated with an application to monitor application transactions. The agent monitors incoming and outgoing application transactions using the agent and transmits monitored transaction data to a monitoring server for anomalous transaction detection. The agent receives instructions from the monitoring server to perform an action based on the transmitted monitored transaction data and reports the status of the performed action to the monitoring server.

Abstract: According to some embodiments, a logical set operator platform may recognize that a user has selected, via a graphical user interface, a sub-set of items from an item set associated with a source application. The logical set operator platform may then receive an indication from the user that a selected logical set operation is to be applied to the item set and to the selected sub-set of items, wherein the selected logical set operation is not implemented by the source application. The selected logical set operation may be applied to create a resulting item set based on the selected sub-set of items, and it then may be arranged for an indication of the resulting item set to be provided to a receiving application.

Abstract: Provided are a device and method of managing data stored in memory. The device may include a buffer for storing data blocks including a head data block, a tail data block, and intermediate data blocks. Non-used blocks may be further included in the buffer between the head data block and the tail data block. The device may further include a controller for managing the data blocks within the buffer. The managing may include determining a shift direction for the data blocks based on a distribution of the data blocks within the buffer, shifting at least one data block from among the data blocks in the determined direction, and shifting the one or more non-used blocks in an opposite direction from which the at least one data block is shifted. As a result of the shifting, the data blocks may be aggregated within the buffer.

Abstract: Aspects of the application relate to configuring of an adapter. Code of the adapter is received and dependencies from the code are determined, wherein at least one of the dependencies includes library code and a version of the library code. A control flow graph is derived from the code and the dependencies. A type of the adapter is determined to, specify how the adapter processes messages. The method further comprises determining at least one implementation of at least one adapter task of the adapter based on the control flow graph. When the determined implementation is not annotated in the code or the control flow graph, the method includes annotating the control flow graph to specify the implementation. A configuration GUI is generated based on the annotated control flow graph and the adapter type. A configuration task may be performed on the adapter according to input received via the configuration GUI.

Abstract: Disclosed herein are embodiments for free-space handling in pages and in-memory containers allowing variable-size data entries. An example system may determine expanses of unallocated space, within a page loaded in memory and configured to allocate a first data entry of a first size within the page that may also allocate at least one subsequent data entry of a second size different from the first size; save, into memory, transient free-space information corresponding to the page, including first position information for a first number of expanses of contiguous unallocated space within the page; evict the page from memory, writing allocated data entries contained therein to persistent storage; store, into persistent storage, persistent free-space information corresponding to the page, including second position information for a second number of expanses of unallocated space within the page, the second number being less than the first number; and discard the transient free-space information.

Abstract: A computer implemented method is provided comprising receiving a group of transaction logs from a first database, allocating transaction logs from the group of transaction logs to a first queue and to a second queue, generating an end-of-group transaction log indicative of an end of the group of transaction logs, allocating the end-of-group log to the first queue and the second queue; replaying transaction logs from the first queue including the end-of-group transaction log allocated to the first queue, replaying transaction logs from the second queue including the end-of-group transaction log allocated to the second queue; and changing visibility of one or more transactions in response to replaying the end-of-group transaction log allocated to the first queue and the end-of-group transaction log allocated to the second queue. Related apparatus, systems, techniques and articles are also described.

Abstract: Described herein includes processing various instruction sets configured for online analytics processing (OLAP) using a calculation engine. This allows OLAP configured instruction sets or calculation scenarios to be efficiently and effectively processed with the calculation engine during run time thereby preventing delays and errors during processing.

Abstract: An identifier of a data source specifying data to be analyzed is determined from a data analysis schema. The data source is called, and data to be analyzed is retrieved. From the data analysis schema, an identifier of a check method to be used to analyze the data is determined. The check method is called and used to analyze the data.

Abstract: A computer-implemented method, a computer-readable medium and a system are provided. A transaction master for each of a plurality of transactions of a database is provided. Each transaction master is configured to communicate with at least one transaction slave to manage execution of a transaction in the plurality of transactions. Each transaction master configured to perform generating a transaction token to specify data to be visible for a transaction on the database, the transaction token including a transaction identifier for identifying whether the transaction is a committed transaction or an uncommitted transaction, receiving a request to commit the transaction, initiating, based on the request, a two-phase commit operation to commit the transaction.

Abstract: Various embodiments of systems, computer program products, and methods to automatically generate low-interaction honeypots to protect application landscapes through are described herein. In an aspect, representative applications associated with resources in a network are identified. The low-interaction honeypots are automatically generated for the identified representative applications. Further, the representative applications are probed to retrieve responses corresponding to different requests. Templates are generated corresponding to request-response pairs by parsing the responses and the requests. During operation, new requests for accessing the resources are responded based on the generated templates. The new requests and corresponding responses are recorded.

Abstract: Techniques are described for graph-based analysis of data generated on sensor networks, such as Internet-of-Things (IoT) networks. Data may be collected from various computing devices, or sensors, on a network. The data is discretized and analyzed to provide a graphical representation of at least a portion of the data. In some instances, the graph may be determined based on various relationships between nodes that correspond to discrete portions of the data, and the relationships between nodes may be time-based correlations between the data of the nodes. The graph accumulates, compresses, and organizes the data to enable efficient data visualization, analysis, alert generation, and/or other activities. A previously generated version of a graph may be compared to a current version to identify a changing situation, such as new usage of the monitored devices, failure or anomalous behavior of the devices, and so forth.