Abstract: An exclusion database is maintained for software discovery scans where directories within a file system are excluded according to discovered software artifacts, scan time parameters, and pre-defined exclusion definitions associated with software applications. A file system tree having directory-specific attributes for causing software discovery scans to limit scanning within the file system.

Abstract: An approach for optimizing single-row operations in a data warehouse. Single-row operations are determined based on receiving database operations. Extends identifiers are received based on the single-row operations. Single-row usage statistics are maintained for extends identifiers based on single-row operations. A logical sequence of the extends identifiers in extends lists stores are sorted based on single-row usage statistics and the logical sequence is maintained based on determining further single-row operations.

Abstract: Identification of unmatched registry entries may be provided by scanning a file system, discovering software, collecting first attribute values of the discovered software, and 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: An exclusion database is maintained for software discovery scans where directories within a file system are excluded according to discovered software artifacts, scan time parameters, and pre-defined exclusion definitions associated with software applications. A file system tree having directory-specific attributes for causing software discovery scans to limit scanning within the file system.

Abstract: One or more processors determine that one or more memory locations in a client computing device contain one or more software artifacts that provide a match to a first software signature. One or more processors send instructions not to scan the one or more memory locations against a second software signature.

Abstract: One or more processors scan a first software container template for one or more identities of software present on a first software container associated with the first software container template. One or more processors generate a map of the one or more identities of software present on the first software container. The one or more identities of software present on the first software container are mapped with one or both of: an identifier of the first software container template and an identifier of the first software container associated with the first software container template.

Abstract: An approach for optimizing single-row operations in a data warehouse. Single-row operations are determined based on receiving database operations. Extends identifiers are received based on the single-row operations. Single-row usage statistics are maintained for extends identifiers based on single-row operations. A logical sequence of the extends identifiers in extends lists stores are sorted based on single-row usage statistics and the logical sequence is maintained based on determining further single-row operations.

Abstract: Identification of unmatched registry entries may be provided by scanning a file system, discovering software, collecting first attribute values of the discovered software, and 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: An approach for optimizing single-row operations in a data warehouse. Single-row operations are determined based on receiving database operations. Extends identifiers are received based on the single-row operations. Single-row usage statistics are stored in extends lists stores where single-row usage statistics include at least one of a hit count and a last hit date. Single-row usage statistics are maintained for extends identifiers based on single-row operations. A logical sequence of the extends identifiers in extends lists stores are sorted based on single-row usage statistics and the logical sequence is maintained based on determining a further single-row operations.

Abstract: One or more processors scan a first software container template for one or more identities of software present on a first software container associated with the first software container template. One or more processors generate a map of the one or more identities of software present on the first software container. The one or more identities of software present on the first software container are mapped with one or both of: an identifier of the first software container template and an identifier of the first software container associated with the first software container template.

Abstract: One or more processors scan a first software container template for one or more identities of software present on a first software container associated with the first software container template. One or more processors generate a map of the one or more identities of software present on the first software container. The one or more identities of software present on the first software container are mapped with one or both of: an identifier of the first software container template and an identifier of the first software container associated with the first software container template.

Abstract: A plurality of software instances deployed in a monitored environment are discovered by a software asset management tool operated by a software asset administrator who is responsible for monitoring software license compliance within the monitored environment. The software asset management tool then collects metrics associated with the plurality of software instances. The collected metrics are then provided to a first analytic service adapted to generate analytic information about the plurality of software instances. Using at least the collected metrics, the analytic service generates analytic information. The analytic information is then obtained from the analytic service. By reviewing the analytic information, the software asset administrator is able to obtain additional insight into the monitored environment that would not otherwise be available to him.

Abstract: One or more processors determine that one or more memory locations in a client computing device contain one or more software artifacts that provide a match to a first software signature. One or more processors send instructions not to scan the one or more memory locations against a second software signature.

Abstract: One or more processors scan a first software container template for one or more identities of software present on a first software container associated with the first software container template. One or more processors generate a map of the one or more identities of software present on the first software container. The one or more identities of software present on the first software container are mapped with one or both of: an identifier of the first software container template and an identifier of the first software container associated with the first software container template.

Abstract: An approach for optimizing single-row operations in a data warehouse. Single-row operations are determined based on receiving database operations. Extends identifiers are received based on the single-row operations. Single-row usage statistics are stored in extends lists stores where single-row usage statistics include at least one of a hit count and a last hit date. Single-row usage statistics are maintained for extends identifiers based on single-row operations. A logical sequence of the extends identifiers in extends lists stores are sorted based on single-row usage statistics and the logical sequence is maintained based on determining a further single-row operations.

Abstract: A plurality of software instances deployed in a monitored environment are discovered by a software asset management tool operated by a software asset administrator who is responsible for monitoring software license compliance within the monitored environment. The software asset management tool then collects metrics associated with the plurality of software instances. The collected metrics are then provided to a first analytic service adapted to generate analytic information about the plurality of software instances. Using at least the collected metrics, the analytic service generates analytic information. The analytic information is then obtained from the analytic service. By reviewing the analytic information, the software asset administrator is able to obtain additional insight into the monitored environment that would not otherwise be available to him.

Abstract: A plurality of software instances deployed in a monitored environment are discovered by a software asset management tool operated by a software asset administrator who is responsible for monitoring software license compliance within the monitored environment. The software asset management tool then collects metrics associated with the plurality of software instances. The collected metrics are then provided to a first analytic service adapted to generate analytic information about the plurality of software instances. Using at least the collected metrics, the analytic service generates analytic information. The analytic information is then obtained from the analytic service. By reviewing the analytic information, the software asset administrator is able to obtain additional insight into the monitored environment that would not otherwise be available to him.

Abstract: A plurality of software instances deployed in a monitored environment are discovered by a software asset management tool operated by a software asset administrator who is responsible for monitoring software license compliance within the monitored environment. The software asset management tool then collects metrics associated with the plurality of software instances. The collected metrics are then provided to a first analytic service adapted to generate analytic information about the plurality of software instances. Using at least the collected metrics, the analytic service generates analytic information. The analytic information is then obtained from the analytic service. By reviewing the analytic information, the software asset administrator is able to obtain additional insight into the monitored environment that would not otherwise be available to him.

Abstract: A plurality of software instances deployed in a monitored environment are discovered by a software asset management tool operated by a software asset administrator who is responsible for monitoring software license compliance within the monitored environment. The software asset management tool then collects metrics associated with the plurality of software instances. The collected metrics are then provided to a first analytic service adapted to generate analytic information about the plurality of software instances. Using at least the collected metrics, the analytic service generates analytic information. The analytic information is then obtained from the analytic service. By reviewing the analytic information, the software asset administrator is able to obtain additional insight into the monitored environment that would not otherwise be available to him.

Abstract: A plurality of software instances deployed in a monitored environment are discovered by a software asset management tool operated by a software asset administrator who is responsible for monitoring software license compliance within the monitored environment. The software asset management tool then collects metrics associated with the plurality of software instances. The collected metrics are then provided to a first analytic service adapted to generate analytic information about the plurality of software instances. Using at least the collected metrics, the analytic service generates analytic information. The analytic information is then obtained from the analytic service. By reviewing the analytic information, the software asset administrator is able to obtain additional insight into the monitored environment that would not otherwise be available to him.