Abstract: According to an aspect of an embodiment, operations include deploying a trigger function on a computing system for detecting an electronic trigger event associated with a first Application Programming Interface (API) provider. The operations further include deploying a rule function for applying at least one trigger rule on event data and deploying an action function for generating at least one API call to a second API provider based on whether the event data satisfies the at least one trigger rule. The operations further include deploying a set of API gateways for enabling a workflow system to invoke at least one of: the deployed trigger function, the deployed rule function, and the deployed action function. The operations further include generating a workflow template of an API mashup based on information associated with the deployed functions and API gateways and posting the generated workflow template to the workflow system.

Abstract: A method may include collecting a plurality of computer-readable source code from an application programming interface (API) repository. The method may also include performing API call code slicing on the computer-readable source code. The method may also include extracting an API host and an endpoint for each of the API call codes identified in the API call code slicing. The method may also include compiling an API mashup database based on the extracted API host and endpoints. Furthermore, the method may also include providing a recommended API mashup of the API mashup database in a user interface.

Abstract: A method may include obtaining metadata associated with first and second data sets that may be stored at remote computing devices. The method may also include constructing a first database based on the metadata, and performing a first processing task on the first data set. The first processing task may include obtaining raw data of the first data set, and importing the raw data of the first data set into a second database that may be configured as a relational database. The first processing task may also include generating relationships in the second database between entries of the first data set to facilitate anticipated responses to queries. The method may additionally include performing a second processing task different from the first processing task on the second data set, and after performing the first processing task, receiving a query that invokes the first data set, and responding to the query.

Abstract: A method may include receiving a selection of an application programming interface (API) for which a task object is to be generated, and obtaining an array of parameters used in the task object, where each element in the array of parameters includes one or more of a constant value, a placeholder value, or combinations thereof, and the placeholder value includes programming to elicit user input to replace the placeholder value during execution of the task object. The method may also include combining the array of parameters with other information for the API for executing the task object into the task object, and storing the task object in a task object database.

Abstract: A method may include obtaining a set of successful responses from one or more tasks, where the tasks include a specific implementation of an API call. The method may also include generating a first schema of a first response of the set of successful responses by extracting information from the first response, the first response responsive to a first task of the one or more tasks. The method may additionally include clustering the first schema with a second schema of a second response of the set of successful responses by applying a learning model to the first and second schemas, where the clustering is based on inputs to the first task and the first response, and creating an integrated task that includes the first task and a second task to which the second response is responsive based on the clustering.

Abstract: A method may include receiving a selection of a task object for execution, the task object related to an application programming interface (API), determining whether the task object includes a placeholder value in the task object, and based on the task object including a placeholder value, producing an interface via which a user submits user input related to the placeholder value as described in the task object. The method may also include replacing the placeholder value with a new value that is based on the user input received via the interface, and generating an API call to the API in a target programming language, where the API call includes the new value. The method may also include deploying the generated API call on a target platform for execution, and obtaining results of the API call.

Abstract: According to an aspect of an embodiment, operations include creating object-oriented software platform by performing a textual analysis of a documentation corpus associated with a set of APIs. The operations further include generating a set of API call objects for an API endpoint of a first API of the set of APIs and constructing a set of natural language descriptors corresponding to the set of API call objects based on the textual analysis. The operations further include generating a set of business objects. Each business object encapsulates conditions applicable on a set of input/output parameters associated with a corresponding API call object of the set of API call objects. The operations further include constructing a software package that encapsulates the set of API call objects, the set of natural language descriptors, and the set of business objects.

Abstract: According to an aspect of an embodiment, operations include receiving a first input corresponding to a selection of one or more Application Programming Interface (API)-based trigger options associated with one or more electronic trigger events. The operations further include receiving a second input corresponding to a selection of one or more trigger rules which are applicable on event data associated with the one or more electronic trigger events and receiving a third input corresponding to a selection of one or more API-based actions. The operations further include constructing an API mashup template based on the first input, the second input, and the third input and generating an API mashup code based on the constructed API mashup template. The API mashup code is configured to be computer-executable on a runtime system.

Abstract: A method includes extracting, from a labelled repository, a plurality of true endpoint descriptions associated with a plurality of web APIs and retrieving a documentation corpus associated with the plurality of web APIs. The method further includes determining a plurality of false endpoint descriptions associated with the plurality of web APIs based on the retrieved documentation corpus and the extracted plurality of true endpoint descriptions. The method further includes extracting feature information associated with the plurality of web APIs, generating a training dataset based on the extracted feature information, and obtaining a ML model based on the generated training dataset. The method further includes providing a set of inputs to the ML model and classifying the provided set of inputs as one of a true description or a false description associated with an endpoint based on a prediction result of the ML model for the provided set of inputs.

Abstract: A method may include iterating over multiple application programming interfaces (APIs) to extract an authentication type for the multiple APIs. The method may also include, from a central repository, automatically registering a new user for access to a given API of the multiple APIs. The method may additionally include obtaining authentication data based on an authentication type for the given API, and storing the authentication data. The method may also include accessing the given API using the stored authentication data.

Abstract: A method may include obtaining a specification for a resource that includes a description of how the resource operates and interacts with another resource. The method may include generating a diagram that includes each word in the description in an order of word types. The method may include generating a second specification that includes the description and the diagram. The method may include generating tasks for the resource. Each task may include a description based on the description of the resource and diagram. The method may include generating hierarchy descriptions for each task based on the task descriptions. The method may include creating a model for each task that includes the hierarchy descriptions for the corresponding task. The hierarchy descriptions may be arranged according to the diagram in the second specification. The method may include presenting one of the hierarchy descriptions for the tasks according to the models.

Abstract: According to an aspect of an embodiment, operations may include receiving a first input corresponding to a selection of a combinatorial optimization problem and receiving a set of datapoints as input. The operations may further include generating a first quadratic unconstrained binary optimization (QUBO) formulation based on an objective function for the combinatorial optimization problem and the received set of datapoints. The operations may further include selecting a first privacy setting and encoding the first QUBO formulation based on the selected privacy setting to generate a second QUBO formulation. The operations may further include submitting the generated second QUBO formulation to an optimization solver machine and receiving a first solution of the second QUBO formulation. The operations may further include decoding the first solution to produce a second solution and publishing an output of the combinatorial optimization problem on a user device based on the second solution.

Abstract: An electronic device receives a first report from a first communication device. The first report is related to a first incident associated with a first vehicle corresponding to the first communication device. The electronic device further receives a second report from a set of second communication devices that lie within a first zonal range of the first vehicle. The electronic device further transmits the first report and the second report to a distributed ledger communicatively coupled to the electronic device. The electronic device further generates consensus information to validate the first incident, based on a smart contract, the received first report, and the received second report. The electronic device further generates a conclusive incident report related to the first incident based on the generated consensus information and generates regulation information based on one of the conclusive incident report, the first report, or the second report, stored on the distributed ledger.

Abstract: According to an aspect of an embodiment, operations include receiving first log data including first information associated with electronic trigger events from a trigger data source. The operations further include extracting trigger output parameters from a first sentence token of the received first log data and displaying a first set of trigger rules onto an electronic User Interface (UI) of a user device based on the extracted trigger output parameters. The operations further include receiving a first input comprising a selection of one or more trigger rules of the displayed first set of trigger rules and receiving a second input comprising a selection of computer-executable actions to be performed based on whether the first information satisfies the one or more trigger rules. The operations further include generating a computer-executable mashup code for execution on a runtime system based on the received first input and the received second input.

Abstract: According to an aspect of an embodiment, operations may include displaying a electronic user interface that includes a plurality of user-selectable options corresponding to taxonomy information for a plurality of optimization problems. The operations may further include receiving a first user input selecting a first template for a specific optimization problem of the plurality of optimization problems. The first user input may include a selection of at least one user-selectable option of the plurality of user-selectable options. The operations may further include receiving a second user input via the selected first template for the specific optimization problem and providing a call to the optimization solver machine to generate a solution for the specific optimization problem based on the received second user input. The second user input may include input data for a plurality of parameters of the specific optimization problem, specified in the selected first template.

Abstract: A method may include obtaining a specification for a resource that includes a description of how the resource operates and interacts with another resource. The method may include generating a diagram that includes each word in the description in an order of word types. The method may include generating a second specification that includes the description and the diagram. The method may include generating tasks for the resource. Each task may include a description based on the description of the resource and diagram. The method may include generating hierarchy descriptions for each task based on the task descriptions. The method may include creating a model for each task that includes the hierarchy descriptions for the corresponding task. The hierarchy descriptions may be arranged according to the diagram in the second specification. The method may include presenting one of the hierarchy descriptions for the tasks according to the models.

Abstract: A method for parameter value resolution, includes extracting, from an application programming interface (API) repository, metadata information associated with an API parameter set of at least one API and generating parameter clusters associated with the API parameter set based on the extracted metadata information. Each parameter cluster may include word tokens associated with at least one API parameter of the API parameters set. The method furthers includes determining a representative term for each parameter cluster and based on the determined representative term, extracting sample parameter values from a knowledge base server. The method further includes generating test API endpoints associated with the at least one API based on the extracted sample parameter values, validating the extracted sample parameter values by executing the generated test API endpoints, and publishing, based on the validation, validation result as an indicator for suitability of the at least one API for a software application.

Abstract: According to an aspect of an embodiment, operations include creating object-oriented software platform by performing a textual analysis of a documentation corpus associated with a set of APIs. The operations further include generating a set of API call objects for an API endpoint of a first API of the set of APIs and constructing a set of natural language descriptors corresponding to the set of API call objects based on the textual analysis. The operations further include generating a set of business objects. Each business object encapsulates conditions applicable on a set of input/output parameters associated with a corresponding API call object of the set of API call objects. The operations further include constructing a software package that encapsulates the set of API call objects, the set of natural language descriptors, and the set of business objects.

Abstract: A method may include receiving first and second application programming interface (API) specifications. The method may include comparing first and second API Specification according to a set of criteria. Responsive to the first and second criteria being identical, the method may include identifying first and second objects. Responsive to the first and second criteria being identical, the method may include classifying a type of the first and second objects and associating one or more parameters in the first and second objects with a consolidated object. The one or more parameters in the first and second objects may be associated with the consolidated object based on the type of the first and second object. The method may include generating a consolidated specification that includes the consolidated object and a description of the one or more parameters of the first and second objects that are associated with the consolidated object in a single API specification.

Abstract: A method of performing graph equation modeling. The method includes receiving an input of a mathematical equation from a user via a user interface. The method also includes using a processor, performing processing on the input of the mathematical equation to decompose the mathematical equation into a plurality of tokens to generate an equation graph corresponding to the mathematical equation. The method also includes automatically generating computer code for a user-specified computing language based on the equation graph. The method also includes causing the automatically generated computer code to be presented to the user via the user interface, the automatically generated computer code corresponding to the inputted mathematical equation defined in a computing environment.