SAP

Methods, systems, and computer-readable storage media for receiving a first job with a first time-series of a first type of historic resource utilization and a second time-series of a second type of historic utilization, receiving a second job with a third time-series of the first type of historic resource utilization and a fourth time-series of the second type of historic utilization, determining a first correlation coefficient between the first time-series and the third time-series, determining a second correlation coefficient between the second time-series and the fourth time-series, combining the first correlation coefficient with the second correlation coefficient to generate a first total correlation coefficient, and in response to the first total correlation coefficient being below a threshold, transmitting the first job and the second job as a first job pair to a first executor of the plurality of job executors to be executed concurrently by the first executor.

Some embodiments are directed scheduling maintenance in a computer system. This may include calculating for future time frame, a risk factor indicative of a likelihood of violation of one or more predefined system performance requirements, the risk factor being based on a predicted quantitative compliance metric and on an estimated impact of the proposed maintenance activity.

A computer-implemented method can receive a vulnerability report for a software. The vulnerability report specifies a vulnerable library used by the software and a path of the vulnerable library within the software. The method can generate a summary of the vulnerability report using a generative artificial intelligence (AI) model, retrieve, from a bug report database, a set of relevant bug reports specifying the vulnerable library, generate a synopsis for the set of relevant bug reports using the generative AI model, generate multiple preliminary decisions on validity of the vulnerability report using the generative AI model based on the summary of the vulnerability report and the synopsis for the set of relevant bug reports, and generate a final decision on validity of the vulnerability report based on the multiple preliminary decisions. Related systems and software for implementing the method are also disclosed.

Each event type in a business process is represented by a node in a process discovery graph. Semantic clustering merges nodes based on a commonality between them. As a result, a graphical user interface (GUI) may be presented that shows fewer nodes. This process may be repeated, using different commonalities at each level. A user may select a node to zoom in, showing the constituent nodes. The frequency of an event or its other attribute values may be compared to a predetermined threshold to determine if the event is a blocking event. The GUI may indicate that the node for an event is a blocking event. When the node for the event is merged with other nodes using semantic clustering, the blocking status of the node is transferred to the merged node. After zooming in on the blocking event, the GUI allows the user to select the blocking event to cause display of a recommendation.

In an example embodiment, a mechanism is provided to allow an LLM to generate multiple text blocks in which different grammars are strictly enforced with a single invocation. This mechanism defines a set of trigger tokens and end tokens. When a trigger token is encountered by the LLM, a strict grammar referenced by the trigger token is begun to be enforced and this enforcement ends when an end token is encountered. Between the time an end token is encountered, and another trigger token is encountered, no grammar is strictly enforced. By including multiple types of such trigger token/end token pairs, it becomes possible for the LLM to generate texts having different strictly enforced grammars in a single invocation.

A system and method include execution of a chatbot session consisting of user queries and chatbot feedbacks, insertion of one of the chatbot feedbacks into an analytics document as analytical insight data, reception of a user selection of one or more of the chatbot feedbacks, generation of a data lineage graph from the selected one or more of the chatbot feedbacks, and storage of the data lineage graph in association with the analytical insight data.

A system and method include receipt of a query from a user, determination, from a plurality of stored text portions, of first text portions which are semantically similar to the query, determination of a first score associated with each of the first text portions, generation of a first prompt based on the first scores, the first prompt including the query and the first text portions, transmission of the first prompt to a text generation model, receipt of a response to the first prompt from the text generation model, presentation of the response and the first text portions, receipt, from the user, of a rating of one of the presented first text portions, and updating of the first score associated with the one of the first text portions based on the rating.

Techniques and solutions are disclosed for managing subprocess versions and their associated components in a computing system. These techniques enable dynamic adaptation and traceability through version control. A subprocess definition is received and updated to reflect modifications to its components, configurations, or execution sequence. Changes are identified and propagated using unique version identifiers and events. Iterative refinement is supported through actions such as validating updated subprocesses, reprocessing data, or maintaining provenance chains. The disclosed solutions provide efficient and structured management of subprocesses.

A computer implemented method receives a query to perform a join operation that joins a first table with a second table based on matching values in a selected column of the first table with values in a selected column of the second table, obtains a first dictionary for the selected column of the first table and a second dictionary for the selected column of the second table, and determines an output size of the join operation based on the first dictionary and the second dictionary. A dictionary for a given column includes a plurality of unique values in the given column and corresponding range indices. A count of a given unique value in the given column is mapped to a range associated with a range index corresponding to the given unique value. Related systems and software for implementing the method are also disclosed.

A transaction which targets an object store employing an open table format (OTF) may be detected by a database execution engine. Next, the database execution engine performs a determination step to determine which OTF enhancement levels to apply to the detected transaction. Then, the database execution engine applies one or more OTF enhancement levels to the transaction based on the determination step. Next, the database execution engine causes the transaction to be processed with the applied one or more OTF enhancement levels. Then, the database execution engine returns a result of the transaction processing to a computing device.