Abstract: Techniques are described for providing and/or managing work routines (WRs) in a collaborative platform. Implementations provide a platform that enables collaboration between multiple entities (e.g., users) to address an issue collectively, for process management, issue resolution, and so forth. The platform enables the creation of a WR that includes any suitable number of data objects to facilitate management of a process, resolution of an issue, and/or other tasks. The WR may also include any suitable number of tools for controlling the manipulation and/or rendering of the data objects. The platform provides a polymorphism through which data objects may be rendered differently based on the tools that are used to render the tool objects. The platform also provides for the automatic creation of a WR, or a template for a WR, where such creation may be triggered by an event and/or based on a current context.

Abstract: Methods and systems are disclosed for flexibly managing lock modes in a data-sharing environment, including optimistic and pessimistic lock modes. A lock mode determination service receives a request from an application instance for a lock mode with which to access specified data objects. The service can determine and provide a suitable lock mode based on a context of the application, and optionally other parameters, by evaluating a checklist of criteria sorted in precedential order. Criteria can include geo-boundaries, platform, role, and others. The requesting application instance uses the determined lock mode to access the data, with optional assistance of a lock service. The lock mode determination service can support one or more applications having one or more instances each, and can also support multiple disjoint data-sharing environments. Suitable environments include cloud, datacenter, mobile, client-server, and SAAS.

Abstract: A database memory manager determines a size class for each of a plurality of memory allocation requests. The memory manager then, based on the determined size classes, assigns which of a plurality of sub-allocators forming part of a plurality of memory pools should handle each memory allocation request. The sub-allocators assignments are based on predefined size ranges for each size class. The corresponding assigned sub-allocators then identify locations within the memory for each memory allocation request. The corresponding assigned sub-allocators next handle the memory allocation requests to allocate memory at the identified locations such that one of the sub-allocators utilizes both thread local storage and core-striped memory management.

Abstract: A system includes reception of a request from a first execution thread to post a message to a second execution thread, a payload of the message comprising an object including a function and serialized text of the function, and, in response to the request, deletion of the function from the object to create a modified object, and calling of a method to post a second message to the second execution thread, a payload of the second message comprising the modified object and the serialized text of the function. A request is received from the second execution thread to handle the second message, the serialized text of the function is deserialized, and the deserialized text of the function is inserted into the modified object to generate a fourth object.

Abstract: A transfer of master data is executed in a backend computing system. The master data includes user data and system data. The transfer of master data includes receiving user data associated with a particular user identifier in the backend computing system, transferring the received user data to an event stream processor, receiving system data associated with a particular log providing computing system in the backend computing system, transferring the received user data to the event stream processor, and executing a transfer of log data associated with logs of computing systems connected to the backend computing system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving source code and an indication that a portion of the source code is insecure. Receiving an annotation to the source code that identifies the indication as being a false positive indication. The annotation includes a logical statement showing that the portion of the source code is not insecure, where the logical statement can be executed by a processor to prove that the portion of the source code is not insecure. Processing the annotation to determine whether the logical statement proves that the portion of the source code is not insecure. In response to determining that the logical statement proves that the portion of the source code is not insecure, retaining the annotation in the source code, and removing the indication that the portion of the source code is insecure.

Abstract: A framework for intelligent memory replacement of loaded data blocks by requested data blocks is provided. For example, various factors are taken into account to optimize the selection of loaded data blocks to be discarded from the memory, in favor of the requested data blocks to be loaded into the memory. In some implementations, correlations between the requested data blocks and the loaded data blocks are used to determine which of the loaded data blocks may become candidates to be discarded from memory.

Abstract: A method is described that involves providing a persisted quantity for a time series time interval to a first transaction, then, providing the same persisted quantity to a second transaction that operates in parallel with the first transaction. The second transaction is not permitted to change the persisted quantity. The method also involves replacing the persisted quantity with a second persisted quantity within the time series. The second persisted quantity is determined by the first transaction. The method also involves writing a persisted quantity change for the time series time interval. The persisted quantity change is determined by the second transaction.

Abstract: A resource registry provides nondeterministic operation environment affording flexible access for resource execution and status monitoring on the cloud. The resource registry service provides generic resource management utilizing registration, updating, and unregistration by resource providers. A requester for an operation may register in the resource registry, an operation resource having parameters defined in metadata. The resource registry notifies a registered resource listener of this registration of the operation resource. The resource listener may then execute the operation according to parameters defined in the operation resource. The resource listener returns a response to the resource registry, concerning a result of execution of the operation. The resource registry updates this status in the metadata of the operation resource. The requester is then able to look up the operation resource's metadata to determine current status of the operation.

Abstract: Systems and methods include determination of a first data analysis period, determination of a first plurality of sets of parameter values, each of the first plurality of sets of parameter values being associated with a respective time period within the first data analysis period and describing a statistical distribution of data points associated with the respective time period, determination of a statistical distribution associated with the first data analysis period based on the first plurality of sets of parameter values, determination of a system condition based on the statistical distribution associated with the first data analysis period, and initiation of an action based on the determined system condition.

Abstract: Techniques are described for forming a machine learning model vector, or just model vector, that represents a weighted combination of machine learning models, each associated with a corresponding feature set and parameterized by corresponding model parameters. A model vector generator generates such a model vector for executing automated machine learning with respect to historical data, including generating the model vector through an iterative selection of values for a feature vector, a weighted model vector, and a parameter vector that comprise the model vector. Accordingly, the various benefits of known and future machine learning algorithms are provided in a fast, effective, and efficient manner, which is highly adaptable to many different types of use cases.

Abstract: Embodiments relate to storing sparse matrices in an in-memory column-oriented database system. Specifically, recent hardware shifts of primary storage from disc into memory, allow execution of linear algebra queries directly in the database engine. Dynamic matrix manipulation operations (like online insertion or deletion of elements) are not covered by most linear algebra frameworks. Therefore a hybrid architecture comprises a read-optimized main structure, and a write-optimized delta structure. The resulting system layout derived from the Compressed Sparse Row (CSR) representation, integrates well with a columnar database design. Moreover, the resulting architecture is amenable to a wide range of non-numerical use cases when dictionary encoding is used. Performance in specific examples is evaluated for dynamic sparse matrix workloads, by applying work flows of nuclear science and network graphs.

Abstract: A calculation engine is described that executes calculation scenarios comprising a plurality of calculation nodes that specify operations to be performed to execute the query. One of the nodes can be a semantic node that is used to modify the query for operations requiring special handling including handling of hierarchy views. Related apparatus, systems, methods, and articles are also described.

Abstract: Example embodiments of compatibility checking for user interface customization are described. In an example embodiment, a first user interface view including first data items is accessed, each of the first data items referencing a corresponding data item of a data source. Whether the first user interface view is referenced by a second user interface view is determined. Based on the first user interface view not being referenced by a second user interface view, changes to any of the first data items of the first user interface view are allowed during a design time of the first user interface view. Based on the first user interface view being referenced by the second user interface view, one or more of the first data items of the first user interface view being referenced by the second user interface view are identified, and changes to the identified data items are prevented.

Abstract: Various embodiments of systems and methods to generate consumer-oriented APIs from a UI model are described herein. In one aspect, a unique identifier is assigned to a node, and corresponding elements and actions of an ADM. The elements and actions associated with the node are mapped to one or more UI elements of an application UI using the assigned unique identifier. A service definition is derived from the UI elements and the UI actions by interacting with the application UI. Further, an API is generated based on the service definition. The generated API is independent from the application UI.

Abstract: Update elements allow logical data object instances, and change requests therefor, to be converted from a first schema to a second schema. For logical data object instances, a transformation function can add nodes to, or remove nodes from a hierarchy of the first schema, or rearrange them. Use of the transformation function can allow second schemas to be defined that change a node hierarchy, yet can be used with existing logical data object instances in the first schema. Changes to logical data object instances can be converted using a mapping or a transformation function, such as a transformation function useable to convert logical data object instances between the first and second schemas. The migration of change requests to the second schema can allow logical data object instances having previously scheduled change requests to be updated from the first schema to the second schema prior to execution of the change request.

Abstract: A number of events are counted in different layers of a computing environment during execution of a software application. The number of counted events can be compared to a previously generated cluster set to determine that at least one of the counted events is an outlier. Data can then be provided that characterizes the at least one of the counted events determined to be an outlier. In some cases, some or all of the functionality of the software application can be selectively disabled. Related apparatus, systems, techniques and articles are also described.

Abstract: Disclosed herein are systems and methods for embedding database procedures in data-driven software applications written in a language different from the database-procedure language. For example, in some embodiments, the hosting application may be written in ABAP whereas the database procedure may be written in SQLScript. In various embodiments, the database procedures are encapsulated in specially marked methods of the host application, which, when called at runtime, cause the database procedures to be created in a database catalog and executed on a database server.

Abstract: Embodiments relate to view caching techniques that cache for a limited time, some of the (intermediate) results of a previous query execution, in order to avoid expensive re-computation of query results. Particular embodiments may utilize a cache manager to determine whether information relevant to a subsequent user request can be satisfied by an existing cache instance or view, or whether creation of an additional cache instance is appropriate. At design time, cache defining columns of a view are defined, with user input parameters automatically being cache defining. Cache instances are created for each tuple of literals for the cache defining columns, and for each explicit or implicit group by clause. Certain embodiments may feature enhanced reuse between cache instances, in order to limit memory footprint. Over time a cache instances may be evicted from memory based upon implementation of a policy such as a Least Recently Used (LRU) strategy.