Abstract: In an approach for providing adaptive software inventory scan frequencies and schedules, a processor receives information from an initial scan of a set of software inventory scans, wherein the information includes at least one of: running processes, file system entries, registry entries, and software catalog evaluations. A processor analyzes the information from the initial scan. A processor predicts an outcome for future software inventory scans based on the analysis of the information, wherein the prediction includes a scanning frequency and a scanning schedule.

Abstract: In an approach for providing adaptive software inventory scan frequencies and schedules, a processor receives information from an initial scan of a set of software inventory scans, wherein the information includes at least one of: running processes, file system entries, registry entries, and software catalog evaluations. A processor analyzes the information from the initial scan. A processor predicts an outcome for future software inventory scans based on the analysis of the information, wherein the prediction includes a scanning frequency and a scanning schedule.

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: Identification of unmatched registry entries may be provided, by scanning a file system, discovering software, collecting first attribute values of the discovered software, receiving a plurality of filtering rules including a method and an attribute. The attribute may comprise a software-specific condition. The method may further comprise collecting native registry entries comprising second attribute values indicated by said attributes of at least one of said rule, and comparing said first attribute values of said discovered software with related ones of said second attribute values of said collected native registry entries. Then, the native registry entries may be grouped into two groups. The first group represents matched registry entries and the second group represents unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery.

Abstract: Installation information of a software component is received. The software component is software. The installation information includes an installation state for the software component, an identifier for the software component, a vendor of the software component, and a calendar date of the installation. The installation information is stored in a pseudo-permanent database. The record of the installation information in the pseudo-permanent database will survive the uninstallation of the software component. An update to the installation information is received in response to the installation state of the software component changing. The update includes modified installation information and a calendar date of when the installation information changed. The updated installation information is stored in the pseudo-permanent database.

Abstract: A first computing entity receives a respective set of software discovery rules from each of a plurality of other computing entities. Based on each of the sets of software discovery rules, a set of software discovery rules associated with the first computing entity is modified. The modified set of software discovery rules is communicated to each of the plurality of other computing entities.

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: Installation information of a software component is received. The software component is software. The installation information includes an installation state for the software component, an identifier for the software component, a vendor of the software component, and a calendar date of the installation. The installation information is stored in a pseudo-permanent database. The record of the installation information in the pseudo-permanent database will survive the uninstallation of the software component. An update to the installation information is received in response to the installation state of the software component changing. The update includes modified installation information and a calendar date of when the installation information changed. The updated installation information is stored in the pseudo-permanent database.

Abstract: In an approach for providing adaptive software inventory scan frequencies and schedules, a processor receives information from an initial scan of a set of software inventory scans, wherein the information includes at least one of: running processes, file system entries, registry entries, and software catalog evaluations. A processor analyzes the information from the initial scan. A processor predicts an outcome for future software inventory scans based on the analysis of the information, wherein the prediction includes a scanning frequency and a scanning schedule.

Abstract: Identification of unmatched registry entries may be provided, by scanning a file system, discovering software, collecting first attribute values of the discovered software, receiving a plurality of filtering rules including a method and an attribute. The attribute may comprise a software-specific condition. The method may further comprise collecting native registry entries comprising second attribute values indicated by said attributes of at least one of said rule, and comparing said first attribute values of said discovered software with related ones of said second attribute values of said collected native registry entries. Then, the native registry entries may be grouped into two groups. The first group represents matched registry entries and the second group represents 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: 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: 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: 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.

Abstract: A method for performing software discovery by an installer controller is provided and may include detecting, at a computer, an attempt by a software installer to execute on the computer, wherein during execution, the software installer modifies software on the computer. A Software Asset Management (SAM) computer server may be queried for an approval status corresponding to a software package provided by the software installer. The installer controller executes the software installer upon receiving on the returned approval status; aggregates a result from the execution of the software installer based on the software installer modifying the software on the computer; and updates a discovery software signature on the computer when the returned approval status is marked as known.

Abstract: A method for performing software discovery by an installer controller is provided and may include detecting, at a computer, an attempt by a software installer to execute on the computer, wherein during execution, the software installer modifies software on the computer. A Software Asset Management (SAM) computer server may be queried for an approval status corresponding to a software package provided by the software installer. The installer controller executes the software installer upon receiving on the returned approval status; aggregates a result from the execution of the software installer based on the software installer modifying the software on the computer; and updates a discovery software signature on the computer when the returned approval status is marked as known.