Abstract: Embodiments are directed to a computer implemented method for generating a drift detector. The method includes generating, using a processor system, drift cases based at least in part on known drift set data of a computer system. The method further includes injecting, using the processor system, the drift cases into the computer system to generate a first data set. The method further includes applying, using the processor system, cleaning rules to the first data set to reduce a size of the first data set and generate a cleaned data set. The method further includes extracting one or more features of the cleaned data set. The method further includes normalizing the extracted one or more features of the cleaned data set. The method further includes training a machine learning system using the extracted and normalized one or more features of the cleaned data, wherein an output of the machine learning system comprises the drift detector.

Abstract: Computer-implemented method for searching for information related to an incident generated in a server system, a system and a computer program product. The method includes extracting context information from a current ticket describing the incident, the context information including a first expression describing a symptom of the incident and indicating at least one component of the server system associated with the symptom; determining a data source which generates data in which the information related to the incident is to be searched for at least according to the at least one component; and using the first expression describing the symptom and a second different expression describing the symptom as keywords to search for the information related to the incident in the data.

Abstract: The scope of the system changes to be considered for analysis for finding problematic changes is reduced in order to allow focusing on highly potential suspicious drifts caused by change sequences. The method and system includes a data cleaning module to remove irrelevant changes, a feature extraction and normalization module to extract the features of change objects, data annotation module to remove irrelevant changes based on patterns, and a clustering module to obtain groups for further analysis. Data cleaning is simplified using domain independent rules. Additional sources of change sequences are removed by application of pattern based techniques so as to narrow down problematic system changes to analyze for root cause analysis. Change error sequence and degree of temporal correlation to correlate system changes with errors, as well as change behavior patterns may be used for downsizing the diagnosis scope.

Abstract: The scope of the system changes to be considered for analysis for finding problematic changes is reduced in order to allow focusing on highly potential suspicious drifts caused by change sequences. The method and system includes a data cleaning module to remove irrelevant changes, a feature extraction and normalization module to extract the features of change objects, data annotation module to remove irrelevant changes based on patterns, and a clustering module to obtain groups for further analysis. Data cleaning is simplified using domain independent rules. Additional sources of change sequences are removed by application of pattern based techniques so as to narrow down problematic system changes to analyze for root cause analysis. Change error sequence and degree of temporal correlation to correlate system changes with errors, as well as change behavior patterns may be used for downsizing the diagnosis scope.

Abstract: Embodiments are directed to a computer implemented method for generating a drift detector. The method includes generating, using a processor system, drift cases based at least in part on known drift set data of a computer system. The method further includes injecting, using the processor system, the drift cases into the computer system to generate a first data set. The method further includes applying, using the processor system, cleaning rules to the first data set to reduce a size of the first data set and generate a cleaned data set. The method further includes extracting one or more features of the cleaned data set. The method further includes normalizing the extracted one or more features of the cleaned data set. The method further includes training a machine learning system using the extracted and normalized one or more features of the cleaned data, wherein an output of the machine learning system comprises the drift detector.

Abstract: Computer-implemented method for searching for information related to an incident generated in a server system, a system and a computer program product. The method includes extracting context information from a current ticket describing the incident, the context information including a first expression describing a symptom of the incident and indicating at least one component of the server system associated with the symptom; determining a data source which generates data in which the information related to the incident is to be searched for at least according to the at least one component; and using the first expression describing the symptom and a second different expression describing the symptom as keywords to search for the information related to the incident in the data.

Abstract: Techniques for scheduling one or more services are provided. The techniques include obtaining customer information, obtaining one or more service characteristics for each of the one or more services, and using the customer information and the one or more service characteristics to schedule the one or more services.

Abstract: Embodiments herein provide a fault-handling scheme based on forward recovery for cooperative workflow environments. The fault handling scheme relies on the correct placement of transaction scopes and their associated fault and compensation handlers for maintaining correct application semantics, a fault propagation scheme for forwarding faults to a workflow component that has the corresponding fault handler, and a distributed mechanism for collecting data of completed workflow components to facilitate recovering from faults. The fault handling scheme makes use of control flow messages to facilitate compensation of nested transaction scopes (residing in different components). The workflow components are also modified with additional code for aiding with fault propagation and fault recovery.

Abstract: Techniques for scheduling one or more services are provided. The techniques include obtaining customer information, obtaining one or more service characteristics for each of the one or more services, and using the customer information and the one or more service characteristics to schedule the one or more services.

Abstract: A technique for orchestrating composite web services in a constrained data flow environment. Data flow constraints represent the restrictions which the domains involved in composition might want to impose on access to the data they provide or the source from which they can accept data. The data flow constraints are overcome by breaking down an input composite web service specification into topologies (a topology is a set of partitions communicatively connected with one another at runtime). The system applies a rule-based filtering mechanism to choose a topology that does not violate any data flow constraints. Each of the partitions belonging to the chosen topology is executed within the same domain as the corresponding web service it invokes, thus having the same access rights as the corresponding web service. The composite web service is orchestrated in a decentralized fashion using these partitions, thereby ensuring that no data flow constraints are violated.

Abstract: The invention provides a method for fault handling in a co-operative workflow environment that employs a placement strategy for transaction scope and associated fault handlers and compensation handlers across different workfiow components. The method employs a fault propagation scheme for forwarding a fault occurring in any of the workflow components to a fault handler. The method employs a distributed data collection mechanism to facilitate recovery from a fault occurring in any the workfiow components. The method employs a fault recovery mechanism using compensation. The transaction scope defines a transaction boundary and provides a fault handling and a fault recovery context for a set of activities and the transaction scope may be nested inside another transaction scope resulting in outer and inner scopes.

Abstract: A structured method of matching schemas that uses multiple levels of ontologies is disclosed. The method maps functions of a target system to a process ontology and maps functions of a source system to the process ontology to produce a first mapping of target functions and source functions using the process ontology. The method identifies target function parameters upon which the target functions operate and identifies source function parameters upon which the source functions operate. Then, the method maps the target function parameters to a concept ontology and maps the source function parameters to the concept ontology to produce a second mapping of the target function parameters and the source function parameters using the concept ontology. This second mapping is enhanced by mapping the target function parameters to a data-type ontology and mapping the source function parameters to the data-type ontology.

Abstract: Embodiments herein provide a fault-handling scheme based on forward recovery for cooperative workflow environments. The fault handling scheme relies on the correct placement of transaction scopes and their associated fault and compensation handlers for maintaining correct application semantics, a fault propagation scheme for forwarding faults to a workflow component that has the corresponding fault handler, and a distributed mechanism for collecting data of completed workflow components to facilitate recovering from faults. The fault handling scheme makes use of control flow messages to facilitate compensation of nested transaction scopes (residing in different components). The workflow components are also modified with additional code for aiding with fault propagation and fault recovery.

Abstract: The invention deals with the enforcement of Service Level Agreement for the services provided over a client-server network. The invention discloses a method, system and a program product for automatic enforcement of SLAs. This is achieved by automatic metering of requests for service and allocation of resources of the server based on the SLA, current available resources and the needs of the customer.

Abstract: A software framework provides building blocks for developing event handlers (typically XML-based or data object based) and a mechanism for dynamically deploying and managing them within an online community having roles and places defined for users and groups. The complex data to be sent/received among users and applications can be described in XML or actual Java™ objects. The software framework is composed of the following principal components: Awarelet base, Awarelet Container, Awarelet Application Adapter, Awarelet Event, Awarelet Configuration, and Awarelet Repository. Awarelet Technology is designed to enhanced the prior art of Instant Messaging in order to facilitate more robust interactions between members of the online community. This invention considers not only users as members, but in addition, business applications and processes as well.

Abstract: The invention deals with the enforcement of Service Level Agreement for the services provided over a client-server network. The invention discloses a method, system and a program product for automatic enforcement of SLAs. This is achieved by automatic metering of requests for service and allocation of resources of the server based on the SLA, current available resources and the needs of the customer.