Various embodiments, methods and systems for implementing a distributed computing system crowdsourcing engine are provided. Initially, a source asset is received from a distributed synthetic data as a service (SDaaS) crowdsource interface. A crowdsource tag is received for the source asset via the distributed SDaaS crowdsource interface. Based in part on the crowdsource tag, the source asset is ingested. Ingesting the source asset comprises automatically computing values for asset-variation parameters of the source asset. The asset-variation parameters are programmable for machine-learning. A crowdsourced synthetic data asset comprising the values for asset-variation parameters is generated.

Various embodiments, methods and systems for implementing a distributed computing system crowdsourcing engine are provided. Initially, a source asset is received from a distributed synthetic data as a service (SDaaS) crowdsource interface. A crowdsource tag is received for the source asset via the distributed SDaaS crowdsource interface. Based in part on the crowdsource tag, the source asset is ingested. Ingesting the source asset comprises automatically computing values for asset-variation parameters of the source asset. The asset-variation parameters are programmable for machine-learning. A crowdsourced synthetic data asset comprising the values for asset-variation parameters is generated.

Systems, methods, and other embodiments associated with enabling client-side enforcement of custom rules when the client is in offline mode include: creating a custom rule for enforcement on a mobile application client on a mobile application server; defining characteristics of user accounts for which the mobile application client is to enforce the custom rule; in response to a connection being established between an instance of the mobile application client for a specific user account and the mobile application server, determining that the instance of the mobile application client should enforce the custom rule based at least in part on a match between characteristics of the specific user account and the defined characteristics; and transmitting the custom rule to the instance of the mobile application client to enable the instance to enforce the custom rule when the instance is operating in the offline mode.

The present invention relates to a method of converting logic written in software code into text, comprising: converting the code to a structured format that represents the logic described in each function of said code as a tree of elements, and mapping the elements of the structured format into corresponding counterparts in a target language for obtaining a text translation of the structured format.

The present invention relates to a method of converting logic written in software code into text, comprising: converting the code to a structured format that represents the logic described in each function of said code as a tree of elements, and mapping the elements of the structured format into corresponding counterparts in a target language for obtaining a text translation of the structured format.

A computer-implemented method includes maintaining one or more databases that collectively store organizational data associated with an organization and an object graph data structure having a plurality of data objects associated with the organizational data. The method further includes generating a formula field which includes one or more dependent fields, wherein the formula field is defined and evaluated using a query expression that makes reference to the object graph data structure. The method further includes, in response to a value of at least one of the one or more dependent fields changing to an updated value, automatically updating a value of the formula field based on the updated value of the at least one of the one or more dependent fields, and enabling inclusion of the formula field in one or more of a report, a policy, a workflow, a trigger, or a rule.

A computer-implemented method includes maintaining one or more databases that collectively store organizational data associated with an organization and an object graph data structure having a plurality of data objects associated with the organizational data. The method further includes generating a formula field which includes one or more dependent fields, wherein the formula field is defined and evaluated using a query expression that makes reference to the object graph data structure. The method further includes, in response to a value of at least one of the one or more dependent fields changing to an updated value, automatically updating a value of the formula field based on the updated value of the at least one of the one or more dependent fields, and enabling inclusion of the formula field in one or more of a report, a policy, a workflow, a trigger, or a rule.

Systems and methods are disclosed for automating and monitoring software development operations. The systems may facilitate a user to submit a request to receive information related to a software application development across a development operations (DevOps) pipeline, and to efficiently receive an accurate response to the request. A natural language processing application may use query parameters from the request to form a query. The query may be sent to an artificial intelligence markup language (AIML) interpreter to retrieve the requested information from a database. Alternatively or additionally, the query may be sent to an application associated with an integration of a plurality of DevOps tools in the DevOps pipeline. The application may develop a dynamic response to the request.

Systems and methods are disclosed for automating and monitoring software development operations. The systems may facilitate a user to submit a request to receive information related to a software application development across a development operations (DevOps) pipeline, and to efficiently receive an accurate response to the request. A natural language processing application may use query parameters from the request to form a query. The query may be sent to an artificial intelligence markup language (AIML) interpreter to retrieve the requested information from a database. Alternatively or additionally, the query may be sent to an application associated with an integration of a plurality of DevOps tools in the DevOps pipeline. The application may develop a dynamic response to the request.

An intent broker component that is configured to facilitate the use of voice to develop code in a source code editor. This is accomplished by using intent parameters that are generated by a natural language processor in response to receiving verbal input from a developer operating with the source code editor. These intent parameters includes an action name and a parameter upon which to perform the named action. The intent parameters are then used to generate input to a code injection component that operates in the source code editor.