Abstract: A method and a related system for identifying unmatched registry entries may be provided. The method may comprise scanning a file system and discovering software based on a file signature, collecting first attributes of the discovered software, collecting native registry entries, and comparing the first attributes against second attributes of the collected registry entries based on a filtering rule. Thereby, the registry entries may be grouped into two groups. One group may represent matched registry entries and the other group may represent unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery.

Abstract: A method and a related system for identifying unmatched registry entries may be provided. The method may comprise scanning a file system and discovering software based on a file signature, collecting first attributes of the discovered software, collecting native registry entries, and comparing the first attributes against second attributes of the collected registry entries based on a filtering rule. Thereby, the registry entries may be grouped into two groups. One group may represent matched registry entries and the other group may represent unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery.

Abstract: A method and a related system for identifying unmatched registry entries may be provided. The method may comprise scanning a file system and discovering software based on a file signature, collecting first attributes of the discovered software, collecting native registry entries, and comparing the first attributes against second attributes of the collected registry entries based on a filtering rule. Thereby, the registry entries may be grouped into two groups. One group may represent matched registry entries and the other group may represent unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery.

Abstract: Software asset management (SAM) for virtual environments performing the following operations: (i) collecting a set of virtual machine (VM) descriptor(s) sets, where each VM descriptor(s) set corresponds to one of the following: a VM appliance or a sealed VM image; (ii) for each VM descriptor(s) set of the set of VM descriptor(s) set(s), determining whether there is a match to an entry in a VM descriptor set/software application mapping data set; and (iii) for each VM descriptor(s) set of the set of VM descriptor(s) set(s), on condition that there is a match, determining an identity of a set of software application(s) in the VM appliance or sealed VM image corresponding to the VM descriptor(s) set based on the respectively matching entry in the VM descriptor/software mapping data set.

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Software asset management (SAM) for virtual environments performing the following operations: (i) collecting a set of virtual machine (VM) descriptor(s) sets, where each VM descriptor(s) set corresponds to one of the following: a VM appliance or a sealed VM image; (ii) for each VM descriptor(s) set of the set of VM descriptor(s) set(s), determining whether there is a match to an entry in a VM descriptor set/software application mapping data set; and (iii) for each VM descriptor(s) set of the set of VM descriptor(s) set(s), on condition that there is a match, determining an identity of a set of software application(s) in the VM appliance or sealed VM image corresponding to the VM descriptor(s) set based on the respectively matching entry in the VM descriptor/software mapping data set.

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: A software asset management method comprising storing URL data for each of a first plurality of software entities, obtaining, by means of a first browser plug-in, first data indicative of a URL from which a browser has obtained content, comparing, for at least one of the first plurality of software entities, the URL data of the respective software entity with the first data, and communicating the first data to a first computer other than a computer hosting the browser subject to a first condition that, for each of the first plurality of software entities, the comparing reveals that the first data does not match the URL data of the respective software entity.

Abstract: A data communication system comprising a first plurality of software entities, each having a respective entity identifier and a respective plurality of characteristics, and a data repository, wherein a first software entity of the first plurality of software entities instigates establishment of a first collection of data at the data repository, the first collection of data having at least one collection identifier selected from the plurality of characteristics of the first software entity, each of a second plurality of the first plurality of software entities having a respective set of the respective plurality of characteristics that matches the at least one collection identifier instigates addition of the entity identifier of the respective software entity to the first collection of data, at least one of the second plurality of software entities instigates addition of data to the first collection of data, and at least one other of the second plurality of software entities obtains a portion of the data from t

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: A method and a related system for identifying unmatched registry entries may be provided. The method may comprise scanning a file system and discovering software based on a file signature, collecting first attributes of the discovered software, collecting native registry entries, and comparing the first attributes against second attributes of the collected registry entries based on a filtering rule. Thereby, the registry entries may be grouped into two groups. One group may represent matched registry entries and the other group may represent unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery.

Abstract: Limiting the number of concurrent requests in a database system. Arranging requests to be handled by the database system in at least one queue. Defining a maximum value (SS) of concurrent requests corresponding to the at least one queue. Monitoring at least one queue utilization parameter corresponding to the at least one queue and calculating a performance value based on the at least one queue utilization parameter. Adapting the maximum value (SS) of concurrent requests of the at least one queue dynamically based on the performance value (PF) in order to improve system performance. Limiting the number of concurrent requests of the at least one queue dynamically based on the dynamically adapted maximum value (SS).

Abstract: An artificial neural network is used to manage software bundling. During a training phase, the artificial neural network is trained using previously bundled software components having known values for identification attributes and known software bundle asociations. Once trained, the artifical neural network can be used to identify the proper software bundles for newly discovered sofware components. In this process, a newly discovered software component having known values for the identification attributes is identified. An input vector is derived from the known values. The input vector is loaded into input neurons of the artificial neural network. A yielded output vector is then obtained from an output neuron of the artificial neural network. Based on the composition of the output vector, the software bundle associated with this newly discovered software component is determined.

Abstract: An artificial neural network is used to manage software bundling. During a training phase, the artificial neural network is trained using previously bundled software components having known values for identification attributes and known software bundle asociations. Once trained, the artifical neural network can be used to identify the proper software bundles for newly discovered sofware components. In this process, a newly discovered software component having known values for the identification attributes is identified. An input vector is derived from the known values. The input vector is loaded into input neurons of the artificial neural network. A yielded output vector is then obtained from an output neuron of the artificial neural network. Based on the composition of the output vector, the software bundle associated with this newly discovered software component is determined.