Abstract: A method, system, and computer program product for running workflows and events using a stateless orchestrator includes: receiving first task data for a first task, where the first task data is information necessary for execution of the first task. The method may also include transmitting a request for a worker node to a provider, where the provider creates the worker node. The method may also include receiving a request from the worker node for the first task data. The method may also include transmitting the first task data to the worker node, where the worker node executes the first task. The method may also include, receiving results of the execution of the first task from the worker node. The method may also include, in response to the receiving the results, transmitting the results to a database.

Abstract: A method, system, and computer program product for running workflows and events using a stateless orchestrator includes: receiving first task data for a first task, where the first task data is information necessary for execution of the first task. The method may also include transmitting a request for a worker node to a provider, where the provider creates the worker node. The method may also include receiving a request from the worker node for the first task data. The method may also include transmitting the first task data to the worker node, where the worker node executes the first task. The method may also include, receiving results of the execution of the first task from the worker node. The method may also include, in response to the receiving the results, transmitting the results to a database.

Abstract: A computer optimizes the prospective generation of data used for analysis of a software problem. The computer generates data in accordance with data generation parameters and a software problem is analyzed with reference to the data so generated. The problem analysis produces a report that details specifics of the software problem, the data that was available for analysis, a flag to indicate success or failure of the analysis to identify a root cause, and information about whether the data supplied was insufficient, sufficient, or superfluous with respect to identifying a root cause of the software problem. The method then uses the analysis report to modify the data generation parameters, thereby iteratively optimizing the data that are generated for analysis of subsequent software problems.

Abstract: A computer optimizes the prospective generation of data used for analysis of a software problem. The computer generates data in accordance with data generation parameters and a software problem is analyzed with reference to the data so generated. The problem analysis produces a report that details specifics of the software problem, the data that was available for analysis, a flag to indicate success or failure of the analysis to identify a root cause, and information about whether the data supplied was insufficient, sufficient, or superfluous with respect to identifying a root cause of the software problem. The method then uses the analysis report to modify the data generation parameters, thereby iteratively optimizing the data that are generated for analysis of subsequent software problems.

Abstract: A computer optimizes the prospective generation of data used for analysis of a software problem. The computer generates data in accordance with data generation parameters and a software problem is analyzed with reference to the data so generated. The problem analysis produces a report that details specifics of the software problem, the data that was available for analysis, a flag to indicate success or failure of the analysis to identify a root cause, and information about whether the data supplied was insufficient, sufficient, or superfluous with respect to identifying a root cause of the software problem. The method then uses the analysis report to modify the data generation parameters, thereby iteratively optimizing the data that are generated for analysis of subsequent software problems.

Abstract: The present invention provides a Dynamic Portal Assembly for Portals which provides the function to manipulate whole topology tree of a Portal at runtime. Topology Fragments, that are partial topology trees, are computed by software components called Adapters and are merged with existing trees at run time. The Adapters themselves can base the computation on the states of External Systems, e.g. Workflow Systems. The introduction of an Independent Adapter Interface allows for easy deployment of new Adapters into the Portal. In a preferred embodiment of the present invention the Dynamic Portal Assembly is adapted to integrate Workflow into Portal without giving awareness to the Portal user.

Abstract: The present invention provides a Dynamic Portal Assembly for Portals which provides the function to manipulate whole topology tree of a Portal at runtime. Topology Fragments, that are partial topology trees, are computed by software components called Adapters and are merged with existing trees at run time. The Adapters themselves can base the computation on the states of External Systems, e.g. Workflow Systems. The introduction of an Independent Adapter Interface allows for easy deployment of new Adapters into the Portal. In a preferred embodiment of the present invention the Dynamic Portal Assembly is adapted to integrate Workflow into Portal without giving awareness to the Portal user.

Abstract: A Dynamic Portal Assembly for Portals for manipulating a topology tree of a Portal at runtime. Topology Fragments, that are partial topology trees, are computed by Adapters and are merged with existing trees at run time. The Adapters base the computation on the states of External Systems, e.g., Workflow Systems. An Independent Adapter Interface allows for easy deployment of new Adapters into the Portal. The Dynamic Portal Assembly is adapted to integrate workflow into a Portal without giving awareness to a Portal user.

Abstract: The present invention provides a Dynamic Portal Assembly for Portals which provides the function to manipulate whole topology tree of a Portal at runtime. Topology Fragments, that are partial topology trees, are computed by software components called Adapters and are merged with existing trees at run time. The Adapters themselves can base the computation on the states of External Systems, e.g. Workflow Systems. The introduction of an Independent Adapter Interface allows for easy deployment of new Adapters into the Portal. In a preferred embodiment of the present invention the Dynamic Portal Assembly is adapted to integrate Workflow into Portal without giving awareness to the Portal user.