Systems and methods for generating functional application designs
First Claim
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1. A computer implemented method for generating functional application designs, the method comprising:
- receiving, by a design tool, one or more natural language utterances corresponding to natural language design commands for editing an application being designed;
editing one or more components of the application being designed based on each of the natural language utterances; and
generating, by the design tool, a functional instance of the application being designed, wherein generating the functional instance of the application being designed comprises;
receiving session data indicative one or more interactions between a user of a test system and the functional instance of the application,determining a goal associated with the application being designed, wherein the goal comprises a purpose of the design, and wherein the session data includes data indicative of whether or not the goal was achieved during testing by the user of the test system,aggregating session data for one or more applications being designed that share the goal,performing a machine learning analysis using the aggregated session data and components of the one or more applications being designed as inputs to train a machine learning model for achieving the goal, anddetermining, by the machine learning based natural language intent processor, the intent of the natural language utterance with respect to the application being designed using the trained machine learning model for achieving the goal.
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Abstract
A method and apparatus for generating functional application designs is described. The method may include receiving one or more natural language utterances corresponding to natural language design commands for editing an application being designed. The method may also include editing one or more components of the application being designed based on each of the natural language utterances. Furthermore, the method may include generating a functional instance of the application being designed.
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Citations
23 Claims
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1. A computer implemented method for generating functional application designs, the method comprising:
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receiving, by a design tool, one or more natural language utterances corresponding to natural language design commands for editing an application being designed; editing one or more components of the application being designed based on each of the natural language utterances; and generating, by the design tool, a functional instance of the application being designed, wherein generating the functional instance of the application being designed comprises; receiving session data indicative one or more interactions between a user of a test system and the functional instance of the application, determining a goal associated with the application being designed, wherein the goal comprises a purpose of the design, and wherein the session data includes data indicative of whether or not the goal was achieved during testing by the user of the test system, aggregating session data for one or more applications being designed that share the goal, performing a machine learning analysis using the aggregated session data and components of the one or more applications being designed as inputs to train a machine learning model for achieving the goal, and determining, by the machine learning based natural language intent processor, the intent of the natural language utterance with respect to the application being designed using the trained machine learning model for achieving the goal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A non-transitory computer readable storage medium including instructions that, when executed by a processor, cause the processor to perform a method for generating functional application designs, comprising:
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receiving, by a design tool, one or more natural language utterances corresponding to natural language design commands for editing an application being designed; editing one or more components of the application being designed based on each of the natural language utterances; and generating, by the design tool, a functional instance of the application being designed, wherein generating the functional instance of the application being designed comprises; receiving session data indicative one or more interactions between a user of a test system and the functional instance of the application, determining a goal associated with the application being designed, wherein the goal comprises a purpose of the design, and wherein the session data includes data indicative of whether or not the goal was achieved during testing by the user of the test system, aggregating session data for one or more applications being designed that share the goal, performing a machine learning analysis using the aggregated session data and components of the one or more applications being designed as inputs to train a machine learning model for achieving the goal, and determining, by the machine learning based natural language intent processor, the intent of the natural language utterance with respect to the application being designed using the trained machine learning model for achieving the goal. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A system for generating functional application designs, the system comprising:
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a memory; and a processor coupled with the memory to; receive one or more natural language utterances corresponding to natural language design commands for editing an application being designed, edit one or more components of the application being designed based on each of the natural language utterances, and generate a functional instance of the application being designed, wherein generate the functional instance of the application being designed comprises; receive session data indicative one or more interactions between a user of a test system and the functional instance of the application, determine a goal associated with the application being designed, wherein the goal comprises a purpose of the design, and wherein the session data includes data indicative of whether or not the goal was achieved during testing by the user of the test system, aggregate session data for one or more applications being designed that share the goal, perform a machine learning analysis using the aggregated session data and components of the one or more applications being designed as inputs to train a machine learning model for achieving the goal, and determine, by the machine learning based natural language intent processor, the intent of the natural language utterance with respect to the application being designed using the trained machine learning model for achieving the goal.
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Specification