Abstract: A system includes a processor that executes computer executable components stored in a memory. The computer executable components can comprise a generation component that generates a GraphQL query. The computer executable components can further comprise a comparison component that compares a predefined GraphQL query to the generated GraphQL query. The computer executable components can further comprise a data mutation component that creates data variations to execute on the predefined GraphQL query and the generated GraphQL query to identify false positives or false negatives of execution equivalence of the queries. The computer executable components can further comprise an evaluation component that compares results of the executed queries to determine sufficiency of the generated GraphQL query.

Abstract: A method, according to one approach, includes: receiving a test sample having schema information and natural language information. The schema information is compared to a pool of entries that correspond to a given query language. One or more entries in the pool that match the schema information of the test sample are identified. One or more entries in the pool that match the natural language information of the test sample are also identified. The method also includes merging selected ones of the entries that match the schema information and selected ones of the entries that match the natural language information. Furthermore, a large language model performs in-context learning using the merged entries and the test sample.

Abstract: A method including employing corporate data to generate an acyclic graph representing a reporting hierarchy, identifying relevant key performance indicators (KPIs) for a plurality of users, training a classifier to predict whether a KPI is relevant to a user of the plurality of users, generating interest-persona maps correlating KPI impact alerts with a subset of the plurality of users based on detected information technology (IT) event streams, business streams, KPI streams, and environmental metrics streams, assigning a score to each KPI impact alert based on compatibility between user features and KPI features, and notifying, by consulting the interest-persona maps, one or more targeted users of the KPI impact alerts relevant to them.