Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: The new creation and use of entitlement constraint templates methods and systems can be linked to software offerings in a software catalog. Allowing software catalog experts to link contractual entitlement data with software product offerings via constraint templates on such a varying list of constraint types, establishes a highly robust software catalog knowledgebase. The result is significant cost savings in terms of time spent inputting entitlement constraint data by contract analysts as well as minimizing errors by those analysts who would otherwise be required to have a very high level of expertise in the software offerings while potentially inputting the same constraint data repeated times.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

Abstract: A software reconciliation engine utilizes a software rule-based catalog to produce accurate license reconciliation across a wide range of software configurations. A software offering may comprise software installables and corresponding constraints. Installed software and active hardware is discovered by a scanner, stored in an installed software database and active hardware database respectively and is mapped against entitled software offerings to determine whether the installed software is entitled to be installed on the hardware. The installed software has a base product attribute, a used-in-count attribute and a parent-child attribute that are used by the reconciliation engine to compare against the constraints to determine entitlement and report compliance.

Abstract: An identification method is provided. The method includes generating dictionaries comprising a product taxonomy and associated base entities comprising sub-sets within a plurality of software products. Data entities are located from unstructured text of the dictionaries. Locating the data entities includes locating long distance word matches within the unstructured text. Ontologies are populated with the entities and relationships between the data entities are determined.

Abstract: An identification method is provided. The method includes generating dictionaries comprising a product taxonomy and associated base entities comprising sub-sets within a plurality of software products. Data entities are located from unstructured text of the dictionaries. Locating the data entities includes locating long distance word matches within the unstructured text. Ontologies are populated with the entities and relationships between the data entities are determined.

Abstract: In a method for determining and scoring a signature for a software package. A processor determines a signature of a first software package, wherein the signature comprises an indication of a first set of files on a computer system after installation of the first software package that were not present on the computer system before the installation, and an indication of a second set of files not remaining on the computer system after an uninstall of the first software package. A processor compares the first and the second set of files indicated in the signature of the first software package to files indicated in one or more other signatures of other software packages. A processor determines a score for the signature of the first software package based on the comparison.

Abstract: In a method for determining and scoring a signature for a software package. A processor determines a signature of a first software package, wherein the signature comprises an indication of a first set of files on a computer system after installation of the first software package that were not present on the computer system before the installation, and an indication of a second set of files not remaining on the computer system after an uninstall of the first software package. A processor compares the first and the second set of files indicated in the signature of the first software package to files indicated in one or more other signatures of other software packages. A processor determines a score for the signature of the first software package based on the comparison.

Abstract: The new creation and use of entitlement constraint templates methods and systems can be linked to software offerings in a software catalog. Allowing software catalog experts to link contractual entitlement data with software product offerings via constraint templates on such a varying list of constraint types, establishes a highly robust software catalog knowledge base. The result is significant cost savings in terms of time spent inputting entitlement constraint data by contract analysts as well as minimizing errors by those analysts who would otherwise be required to have a very high level of expertise in the software offerings while potentially inputting the same constraint data repeated times.

Abstract: The new creation and use of entitlement constraint templates methods and systems can be linked to software offerings in a software catalog. Allowing software catalog experts to link contractual entitlement data with software product offerings via constraint templates on such a varying list of constraint types, establishes a highly robust software catalog knowledgebase. The result is significant cost savings in terms of time spent inputting entitlement constraint data by contract analysts as well as minimizing errors by those analysts who would otherwise be required to have a very high level of expertise in the software offerings while potentially inputting the same constraint data repeated times.

Abstract: In a method for determining signatures for a software package, a processor compares files on a computer system after an installation of a software package to files on the computer system before the installation. The processor determines a signature of the software package. The signature includes an indication of files on the computer system after the installation of the software package that were not present on the computer system before the installation. The processor compares files remaining on the computer system after an uninstall of the first software package to the files on the computer system after the installation of the first software package. The processor determines one or more files indicated in the first signature not remaining on the computer system after the uninstall of the first software package.

Abstract: An identification method is provided. The method includes generating dictionaries comprising a product taxonomy and associated base entities comprising sub-sets within a plurality of software products. Data entities are located from unstructured text of the dictionaries. Locating the data entities includes locating long distance word matches within the unstructured text. Ontologies are populated with the entities and relationships between the data entities are determined.