Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.

Abstract: A method and apparatus for recursive navigation. In one embodiment of the method, a first reply is generated in response to receiving a first request from a mobile device. The first reply is generated as a function of a page definition, and the first reply comprises data selected from a first object of a logical data model, but not a second object of the logical data model. The first and second objects are distinct from each other. A second reply is generated in response to receiving a second request from the mobile device. The second reply is generated as a function of the page definition, and the second reply comprises data selected from the second object but not the first object.

Abstract: In one embodiment, a method includes accessing a mapping that represents a correspondence between a column in a source database and a column in a temporary storage table, in response to receiving a data operation request to execute a data operation on a column of the source database. The method further includes changing the temporary storage table by executing the data operation on the temporary storage table and performing a reconstruction operation using data from the temporary storage table and the source database.

Abstract: In one embodiment, a method for refining a business process model includes receiving business process data pertaining to a first phase of a business process definition from a first class of users, creating a model of a business process using the business process data received from the first class of users, receiving business process data pertaining to a second phase of the business process definition from a second class of users, and augmenting the model of the business process based on the business process data received from the second class of users. The method further includes iteratively refining the model of the business process in response to input provided by the first class of users and/or the second class of users.

Abstract: An application defined to allow polymorphic serialization. In one embodiment, the application comprises a plurality of page definitions or views. At least one page definition is configured to be serialized into content in a first serialization format and content in a second serialization format that is different from the first serialization.

Abstract: A method for pre-rendering a system response. In one embodiment, the method includes a mobile device sending a first page request to a secondary system via a wireless communication link. The secondary system sends a first reply to the mobile device in response to the secondary system receiving the first page request, wherein the first reply comprises first page information and second page information. The mobile device stores the second page information in memory. The mobile device also displays a first page comprising a visual representation of the first page information.

Abstract: Polymorphic serialization is disclosed. In one embodiment polymorphic serialization may include generating a first reply in response to receiving a first request from a first device, the first reply including first content in a first serialization format. The first reply is transmitted to the first device via a first communication link. A second reply may be generated in response to receiving a second request from a second device, the second reply including second content in a second serialization format. The second reply is transmitted to the second device via a second communication link. The first and second devices are distinct from each other, and the first and second serialization formats are distinct from each other.

Abstract: A method is disclosed in which a server generates and transmits a reply to a mobile device via a wireless communication link in response to receiving a request from a mobile device. The reply includes first pattern information and data elements retrieved from a logical data model. The mobile device renders a first page on a screen thereof in response to receiving the reply. The first page includes visual representations of the data elements, and the first page presents the visual representations in a first pattern corresponding to the first pattern information.

Abstract: In one embodiment, a method for refining a business process model includes receiving business process data pertaining to a first phase of a business process definition from a first class of users, creating a model of a business process using the business process data received from the first class of users, receiving business process data pertaining to a second phase of the business process definition from a second class of users, and augmenting the model of the business process based on the business process data received from the second class of users. The method further includes iteratively refining the model of the business process in response to input provided by the first class of users and/or the second class of users.

Abstract: In one embodiment, a method for refining a business process model includes receiving business process data pertaining to a first phase of a business process definition from a first class of users, creating a model of a business process using the business process data received from the first class of users, receiving business process data pertaining to a second phase of the business process definition from a second class of users, and augmenting the model of the business process based on the business process data received from the second class of users. The method further includes iteratively refining the model of the business process in response to input provided by the first class of users and/or the second class of users.

Abstract: To enable language-level integration of multiple programming languages into a single programming framework, one or more domain specific languages (DSLs) are specified as incremental extensions to a host programming language. An application created in this framework may include program code written in the host language as well as DSL inset code that is written in any of the DSLs. The extensions to the host language are described in DSL specifications, which define how the DSL inset code is processed. At runtime, DSL inset code in the source code is detected and passed to a DSL inset processor for execution according to an appropriate DSL specification, whereas source code in the host language is executed by a host language processor.

Abstract: In one embodiment, a business process meta-model is defined that represents a business process. The business process meta-model includes control flow elements pertaining to a control flow of the business process, and annotation elements providing details for the control flow elements.

Abstract: In one embodiment, a method for providing multiple views of a business process definition includes storing a model of a business process, and providing different view points of the model to different classes of users.

Abstract: In one embodiment, a method for facilitating long-lived data transactions includes starting a data transaction during a first user session, storing data associated with the data transaction in a temporary storage table, and ending the data transaction during a second user session using contents of the temporary storage table.