Abstract: A device may obtain information identifying a base application. The device may extract a set of sub-application artifacts associated with the base application based on structural information associated with the base application. The device may define a set of metadata attributes associated with the set of sub-application artifacts associated with the base application. The device may generate a set of hash tuples for the set of metadata attributes associated with the set of sub-application artifacts associated with the base application. The device may generate a base composite identity of the base application based on the set of hash tuples. The device may store the base composite identity in a blockchain and in connection with storage of the base application in the blockchain to enable subsequent identification and verification of the base application.

Abstract: A method and a system are provided for auto-allocation of one or more tasks to one or more resources of an organization. The method includes receiving one or more requests from a requestor computing device associated with the organization over a communication network. The one or more requests may include at least one or more first attributes of the one or more tasks and one or more pre-defined constraints. The method further includes extracting one or more second attributes associated with the one or more resources based on at least the one or more first attributes of the one or more tasks. The method further includes determining an allocation of the one or more tasks to the one or more resources based on at least the one or more first attributes and the one or more second attributes, such that the one or more predefined constraints are satisfied.

Abstract: A device may obtain information identifying a base application. The device may extract a set of sub-application artifacts associated with the base application based on structural information associated with the base application. The device may define a set of metadata attributes associated with the set of sub-application artifacts associated with the base application. The device may generate a set of hash tuples for the set of metadata attributes associated with the set of sub-application artifacts associated with the base application. The device may generate a base composite identity of the base application based on the set of hash tuples. The device may store the base composite identity in a blockchain and in connection with storage of the base application in the blockchain to enable subsequent identification and verification of the base application.

Abstract: A device may receive, from a user device, a request to verify a machine learning (ML) application using a metamorphic testing procedure. The device may determine a type of ML process used by the ML application, and may select one or more metamorphic relations (MRs), to be used for performing the metamorphic testing procedure, based on the type of ML process. The device may receive test data to be used to test the ML application, wherein the test data is based on the one or more MRs, and may perform, by using the one or more MRs and the test data, the metamorphic testing procedure to verify one or more aspects of the ML application. The device may generate a report that indicates whether the one or more aspects of the ML application have been verified and may provide the report for display on an interface of the user device.

Abstract: The disclosed embodiments illustrate methods and systems for generating recommendations for client process execution of one or more client processes corresponding to a plurality of clients of an organization. The method comprises retrieving an event log including event data captured during execution of one or more processes in the organization to service a plurality of clients of a predefined type. The event log is analyzed across the plurality of clients to determine cross-clientele information including a process compliance deviation between an observed and an expected client process execution of the one or more processes. Thereafter, a set of root-causes of the process compliance deviation is determined based on process models of the one or more processes and/or decision rules of the organization. Further, one or more recommendations for the client process execution of the one or more processes of the organization are generated, based on the set of root-causes.

Abstract: A device may receive, from a user device, a request to verify a machine learning (ML) application using a metamorphic testing procedure. The device may determine a type of ML process used by the ML application, and may select one or more metamorphic relations (MRs), to be used for performing the metamorphic testing procedure, based on the type of ML process. The device may receive test data to be used to test the ML application, wherein the test data is based on the one or more MRs, and may perform, by using the one or more MRs and the test data, the metamorphic testing procedure to verify one or more aspects of the ML application.

Abstract: The disclosed embodiments illustrate methods and systems for crowdsourcing a task. The method includes identifying a first set of workers from workers, based on a performance of the workers on a set of tasks previously attempted by the workers, and a Service Level Agreement (SLA) associated with the task. The method further includes generating a graph comprising nodes and edges connecting the nodes. Each of the one or more nodes is indicative of a worker. An edge, connecting two workers, is indicative of said two workers having worked together on at least one task. The method further includes receiving an input, to select a second set of workers from the first set of workers, based on one or more first parameters associated with each of the nodes in said graph and second parameters associated with each of the edges in the graph.

Abstract: A system for recognizing processes performed by a call center agent during a session may collect input data by initiating a screen capture logging thread to capture screen shots of a desktop of the electronic device during a session. The system analyzes the input data to generate one or more events, generates a mid-level event log comprising one or more of the events, and performs action recognition on the mid-level event log to ascertain one or more actions that were performed within the one or more graphical user interfaces by the call center agent during the session.

Abstract: The disclosed embodiments illustrate methods and systems for generating recommendations for client process execution of one or more client processes corresponding to a plurality of clients of an organization. The method comprises retrieving an event log including event data captured during execution of one or more processes in the organization to service a plurality of clients of a predefined type. The event log is analyzed across the plurality of clients to determine cross-clientele information including a process compliance deviation between an observed and an expected client process execution of the one or more processes. Thereafter, a set of root-causes of the process compliance deviation is determined based on process models of the one or more processes and/or decision rules of the organization. Further, one or more recommendations for the client process execution of the one or more processes of the organization are generated, based on the set of root-causes.

Abstract: A method and a system are provided for role-based auto-selection of employees for trainings associated with skills required in a project. The method comprising receiving a request for the project. The method may extract one or more current skills of one or more employees based on the received request. The method for a required role in a project may further determine, a proficiency gap between the one or more required skills and the one or more current skills for each of the one or more employees. The method for a required role in a project may prioritize the one or more required skills for each of the one or more employees based on the determined proficiency gap. The method may select a set of employees from the one or more employees for one or more skill-based trainings.

Abstract: A method and a system are provided for auto-allocation of one or more tasks to one or more resources of an organization. The method includes receiving one or more requests from a requestor computing device associated with the organization over a communication network. The one or more requests may include at least one or more first attributes of the one or more tasks and one or more pre-defined constraints. The method further includes extracting one or more second attributes associated with the one or more resources based on at least the one or more first attributes of the one or more tasks. The method further includes determining an allocation of the one or more tasks to the one or more resources based on at least the one or more first attributes and the one or more second attributes, such that the one or more predefined constraints are satisfied.

Abstract: A system for recognizing processes performed by a call center agent during a session collects from one or more input devices in communication with the electronic device, input data that includes data pertaining to one or more interactions that a call center agent has with one or more programs running on the electronic device that cause one or more graphical user interfaces to be displayed on a desktop of the electronic device during a session. The system analyzes the input data to generate one or more events and a mid-level event log having one or more of the events, and performs action recognition on the mid-level event log to ascertain one or more actions that were performed within the one or more graphical user interfaces by the call center agent during the session.

Abstract: Techniques enabling an end-user to specify complex concepts consisting of code abstractions, design abstractions and architectural abstractions in rule form are disclosed. In one embodiment, a graphical user interface is provided to guide a user through the process of entering concept specification information in order to define concepts, including the provision of one or more code snippets that are subsequently analyzed to assist the user in specifying the concept. The resulting rules or concept signatures are evaluated by a rule engine to determine the degree to which the underlying concepts are reflected in a given set of code. Recommended measures that need to be taken for transforming code to satisfy a concept may be provided subsequent to the analysis of the code. In this manner, code quality may be improved through systematic analysis of targeted code to demonstrate adherence (or non-adherence, as the case may be) to user-defined concepts.

Abstract: A method and a system are provided for creating a summarized multimedia content. The method extracts one or more frames from a plurality of frames in a multimedia content based on a measure of area occupied by a text content in a portion of each of the plurality of frames. The method selects one or more sentences from an audio content associated with the multimedia content based on at least a weight associated with a plurality of words present in the audio content. The method extracts one or more audio segments from the audio content associated with the multimedia content based on one or more parameters associated with the audio content. The method creates the summarized multimedia content based on the one or more frames, the one or more sentences, and the one or more audio segments.

Abstract: Systems and methods receive manually created event logs that include manually entered data of executed processes, and such systems and methods automatically identify errors in the event logs (based on whether the data violates expected log content). The systems and methods classify the errors, prioritize the event logs into a priority order (based on a previously established error priority ranking), and output the event logs classified into different classifications (and in priority order). The systems and methods receive feedback in order to alter the priority order and the different classifications of the event logs. Further, these systems and methods automatically generate recommendations to correct the errors, using different recommendation processes based on the classifications of the errors. The event logs are output in the different classifications and in the priority order, and the locations of the errors within the event logs are identified by the systems and methods herein.

Abstract: A method of generating a cell design of print production devices for a print production environment includes receiving a print job list, and identifying a plurality of print production devices located in the production environment. The system identifies a list of functions associated with the print jobs, and generates a graph. The system determines a threshold value, and partitions the graph into a number of groups equal to the threshold value such that a number of edges extending between groups is minimized. The system generates an initial cell design for the print production environment, and causes a hardware setting of each of the plurality of production devices to be updated to reflect the cell to which the production device was assigned and to enable the production device to perform one or more functions associated with the cell to which the production device was assigned.

Abstract: The disclosed embodiments illustrate methods and systems for crowdsourcing a task. The method includes identifying a first set of workers from workers, based on a performance of the workers on a set of tasks previously attempted by the workers, and a Service Level Agreement (SLA) associated with the task. The method further includes generating a graph comprising nodes and edges connecting the nodes. Each of the one or more nodes is indicative of a worker. An edge, connecting two workers, is indicative of said two workers having worked together on at least one task. The method further includes receiving an input, to select a second set of workers from the first set of workers, based on one or more first parameters associated with each of the nodes in said graph and second parameters associated with each of the edges in the graph.

Abstract: Systems and methods receive manually created event logs that include manually entered data of executed processes, and such systems and methods automatically identify errors in the event logs (based on whether the data violates expected log content). The systems and methods classify the errors, prioritize the event logs into a priority order (based on a previously established error priority ranking), and output the event logs classified into different classifications (and in priority order). The systems and methods receive feedback in order to alter the priority order and the different classifications of the event logs. Further, these systems and methods automatically generate recommendations to correct the errors, using different recommendation processes based on the classifications of the errors. The event logs are output in the different classifications and in the priority order, and the locations of the errors within the event logs are identified by the systems and methods herein.

Abstract: Techniques enabling an end-user to specify complex concepts consisting of code abstractions, design abstractions and architectural abstractions in rule form are disclosed. In one embodiment, a graphical user interface is provided to guide a user through the process of entering concept specification information in order to define concepts, including the provision of one or more code snippets that are subsequently analyzed to assist the user in specifying the concept. The resulting rules or concept signatures are evaluated by a rule engine to determine the degree to which the underlying concepts are reflected in a given set of code. Recommended measures that need to be taken for transforming code to satisfy a concept may be provided subsequent to the analysis of the code. In this manner, code quality may be improved through systematic analysis of targeted code to demonstrate adherence (or non-adherence, as the case may be) to user-defined concepts.

Abstract: Techniques enabling an end-user to specify complex concepts consisting of code abstractions, design abstractions and architectural abstractions in rule form are disclosed. In one embodiment, a graphical user interface is provided to guide a user through the process of entering concept specification information in order to define concepts, including the provision of one or more code snippets that are subsequently analyzed to assist the user in specifying the concept. The resulting rules or concept signatures are evaluated by a rule engine to determine the degree to which the underlying concepts are reflected in a given set of code. Recommended measures that need to be taken for transforming code to satisfy a concept may be provided subsequent to the analysis of the code. In this manner, code quality may be improved through systematic analysis of targeted code to demonstrate adherence (or non-adherence, as the case may be) to user-defined concepts.