Abstract: In non-limiting examples of the present disclosure, systems and methods for rewriting expressions utilizing cooperative visitors are provided. A data request may be received by a computing device, which may then be represented in a data structure, e.g., an expression tree, representative of the data request. A node within the data structure representative of the data request may be visited. Metadata associated with at least one cooperative visitor may be extracted from the node, and the node may then be transformed by applying the at least one cooperative visitor to the node.

Abstract: Representative embodiments disclosed compress expressions so they utilize less physical storage. An expression is placed in a standard representation, such as an expression tree. The system utilizes one or more rules to identify portions of the expression that are likely to be common to other expressions. The common portions are extracted from the expression tree as a template and the remaining portions are hoisted from the expression as unique portions. If the template does not already reside in a cache, the template is stored in the cache. A cache reference is obtained for the template and combined with the unique portions to create a bundle that reduces storage requirements for the expression. The original expression is recovered by retrieving the template from the cache using the cache reference and placing the hoisted unique portions into their original locations in the template.

Abstract: A technique is described herein for facilitating a client's interaction with a machine-consumable resource, such as, but not limited to, a database, a service (or microservice), user interface-related information used to construct a consumer-side user interface presentation, etc. The technique includes a definition phase and a consummation phase. In the definition phase, the technique can produce different sets of attributes. Each set of attributes complements a particular target consumption environment. In the consumption phase, the technique determines the characteristics of the consumption environment that a consumer is currently using. The technique then retrieves an appropriate set (or sets) of attributes associated with that consumption environment, and uses the retrieved set(s) to provide an appropriate user experience to the consumer.

Abstract: In non-limiting examples of the present disclosure, systems and methods for interning expression trees are provided. Hash code for a plurality of expression tree nodes is recursively computed and a determination is made as to whether hash code for each of a plurality of expression tree nodes is stored in a cached intern pool. Upon determining that at least one of a plurality of expression tree nodes is not stored in a cached intern pool, one or more functions may be run on at least one of a plurality of expression tree nodes for determining whether at least one of a plurality of expression tree nodes should be stored in a cached intern pool. Normalization of expression trees may also be employed to effectuate effective sharing of expression tree nodes.

Abstract: Representative embodiments disclosed compress expressions so they utilize less physical storage. An expression is placed in a standard representation, such as an expression tree. The system utilizes one or more rules to identify portions of the expression that are likely to be common to other expressions. The common portions are extracted from the expression tree as a template and the remaining portions are hoisted from the expression as unique portions. If the template does not already reside in a cache, the template is stored in the cache. A cache reference is obtained for the template and combined with the unique portions to create a bundle that reduces storage requirements for the expression. The original expression is recovered by retrieving the template from the cache using the cache reference and placing the hoisted unique portions into their original locations in the template.

Abstract: In non-limiting examples of the present disclosure, systems and methods for rewriting expressions utilizing cooperative visitors are provided. A data request may be received by a computing device, which may then be represented in a data structure, e.g., an expression tree, representative of the data request. A node within the data structure representative of the data request may be visited. Metadata associated with at least one cooperative visitor may be extracted from the node, and the node may then be transformed by applying the at least one cooperative visitor to the node.

Abstract: In non-limiting examples of the present disclosure, systems and methods for interning expression trees are provided. Hash code for a plurality of expression tree nodes is recursively computed and a determination is made as to whether hash code for each of a plurality of expression tree nodes is stored in a cached intern pool. Upon determining that at least one of a plurality of expression tree nodes is not stored in a cached intern pool, one or more functions may be run on at least one of a plurality of expression tree nodes for determining whether at least one of a plurality of expression tree nodes should be stored in a cached intern pool. Normalization of expression trees may also be employed to effectuate effective sharing of expression tree nodes.

Abstract: Technologies pertaining to retrieval of contextually relevant attribute values for an automatically identified named entity in a document are described herein. Named entity recognition technologies are employed to identify named entities in the text of a document. Context corresponding to an identified named entity is analyzed to probabilistically assign a class to the named entity. Attributes that are most relevant to the class are determined, and attribute values for such attributes are retrieved. The attribute values are presented in correlation with the named entity in the document responsive to user-selection of the named entity in the document.

Abstract: Technologies pertaining to retrieval of contextually relevant attribute values for an automatically identified named entity in a document are described herein. Named entity recognition technologies are employed to identify named entities in the text of a document. Context corresponding to an identified named entity is analyzed to probabilistically assign a class to the named entity. Attributes that are most relevant to the class are determined, and attribute values for such attributes are retrieved. The attribute values are presented in correlation with the named entity in the document responsive to user-selection of the named entity in the document.