Abstract: In accordance with an embodiment, described herein are systems and methods for auto-completion of ICS flow using artificial intelligence/machine learning. Next actions prediction is a service that assists users in modeling the flows quickly by predicting and suggesting the next set of actions a user might be thinking of adding. The service also assists the user to follow some of the best practices while creating an integration flow.

Abstract: Techniques for transforming plug-in application recipe (PIAR) variables are disclosed. A PIAR definition identifies a trigger and an action. Trigger variable values, exposed by a first plug-in application, are necessary to evaluate the trigger. Evaluating the trigger involves determining whether a condition is satisfied, based on values of trigger variables. A second plug-in application exposes an interface for carrying out an action. Evaluating the action involves carrying out the action based on input variable values. A user selects, via a graphical user interface of a PIAR management application, a variable for a trigger or action operation and a transformation operation to be applied to the variable. The PIAR management application generates a PIAR definition object defining the trigger, the action, and the transformation operation, and stores the PIAR definition object for evaluation on an ongoing basis.

Abstract: In accordance with an embodiment, described herein are systems and methods for auto-completion of ICS flow using artificial intelligence/machine learning. Next actions prediction is a service that assists users in modeling the flows quickly by predicting and suggesting the next set of actions a user might be thinking of adding. The service also assists the user to follow some of the best practices while creating an integration flow.

Abstract: In accordance with an embodiment, described herein are systems and methods for auto-completion of ICS flow using artificial intelligence/machine learning. Next actions prediction is a service that assists users in modeling the flows quickly by predicting and suggesting the next set of actions a user might be thinking of adding. The service also assists the user to follow some of the best practices while creating an integration flow.

Abstract: In accordance with an embodiment, described herein are systems and methods for auto-completion of ICS flow using artificial intelligence/machine learning. Next actions prediction is a service that assists users in modeling the flows quickly by predicting and suggesting the next set of actions a user might be thinking of adding.

Abstract: Techniques for transforming plug-in application recipe (PIAR) variables are disclosed. A PIAR definition identifies a trigger and an action. Trigger variable values, exposed by a first plug-in application, are necessary to evaluate the trigger. Evaluating the trigger involves determining whether a condition is satisfied, based on values of trigger variables. A second plug-in application exposes an interface for carrying out an action. Evaluating the action involves carrying out the action based on input variable values. A user selects, via a graphical user interface of a PIAR management application, a variable for a trigger or action operation and a transformation operation to be applied to the variable. The PIAR management application generates a PIAR definition object defining the trigger, the action, and the transformation operation, and stores the PIAR definition object for evaluation on an ongoing basis.

Abstract: Techniques for transforming plug-in application recipe (PIAR) variables are disclosed. A PIAR definition identifies a trigger and an action. Trigger variable values, exposed by a first plug-in application, are necessary to evaluate the trigger. Evaluating the trigger involves determining whether a condition is satisfied, based on values of trigger variables. A second plug-in application exposes an interface for carrying out an action. Evaluating the action involves carrying out the action based on input variable values. A user selects, via a graphical user interface of a PIAR management application, a variable for a trigger or action operation and a transformation operation to be applied to the variable. The PIAR management application generates a PIAR definition object defining the trigger, the action, and the transformation operation, and stores the PIAR definition object for evaluation on an ongoing basis.

Abstract: Techniques for managing a plug-in application recipe (“PIAR”) are disclosed. A mapping between (a) a user-selected field, selected via a PIAR creation interface, and (b) a third-party application field, exposed by an application programming interface (“API”) of a third-party application, is stored. The third-party application field is associated with a trigger or action of a PIAR. Managing the PIAR in an active state involves periodically receiving and checking data from the third-party application field against a PIAR condition. During or after managing the PIAR in the active state, information is stored to update the mapping to a different mapping. The different mapping maps the user-selected field to a different third-party application field. Without modifying the PIAR, managing the PIAR in the active state then involves periodically receiving and checking data from the different third-party application field against the PIAR condition.

Abstract: Techniques for managing a plug-in application recipe (“PIAR”) are disclosed. A mapping between (a) a user-selected field, selected via a PIAR creation interface, and (b) a third-party application field, exposed by an application programming interface (“API”) of a third-party application, is stored. The third-party application field is associated with a trigger or action of a PIAR. Managing the PIAR in an active state involves periodically receiving and checking data from the third-party application field against a PIAR condition. During or after managing the PIAR in the active state, information is stored to update the mapping to a different mapping. The different mapping maps the user-selected field to a different third-party application field. Without modifying the PIAR, managing the PIAR in the active state then involves periodically receiving and checking data from the different third-party application field against the PIAR condition.

Abstract: Techniques for transforming plug-in application recipe (PIAR) variables are disclosed. A PIAR definition identifies a trigger and an action. Trigger variable values, exposed by a first plug-in application, are necessary to evaluate the trigger. Evaluating the trigger involves determining whether a condition is satisfied, based on values of trigger variables. A second plug-in application exposes an interface for carrying out an action. Evaluating the action involves carrying out the action based on input variable values. A user selects, via a graphical user interface of a PIAR management application, a variable for a trigger or action operation and a transformation operation to be applied to the variable. The PIAR management application generates a PIAR definition object defining the trigger, the action, and the transformation operation, and stores the PIAR definition object for evaluation on an ongoing basis.