Abstract: A system includes a processor configured to perform operations, including determining, for each respective software defect of software defects identified in a software product, corresponding attribute values that represent a software development history of the respective software defect, and determining, for each respective defect, using a machine learning model, and based on the corresponding attribute values, a corresponding escalation value representing a likelihood of the respective defect being escalated for resolution after release of the software product. The machine learning model may have been trained using corresponding software development histories of training defects that were escalated for resolution after release of a prior version of the software product.

Abstract: Methods and systems for configuring a main or security processor in a customer premises equipment (CPE) with an encrypted seed for password-of-the-day (PoTD) processing is described. A CPE includes a modem processor, a main processor, and a PoTD component included on the main processor. The main processor receives, via the modem processor from a user device, an access request to the CPE. In response to the access request, the PoTD component accesses an encrypted seed stored on the main processor, generates a PoTD from the encrypted seed, and provides an access response based on comparison of the generated PoTD with a PoTD provided via the user device. A security processor can be used in lieu of the main processor. The PoTD component is then included in the security processor and the encrypted seed is then stored on the security processor.

Abstract: Described is a system (and method) for specialized data management when performing incremental backups to a cloud-based object storage. When backing up client data, the server may utilize incremental backups to conserve the amount of storage space required on the object storage. However, the server may implement a configuration that enables full reconstruction of the client data at the time of recovery. To provide such capabilities, the server may leverage a specialized metadata database. The metadata database may be an embedded database maintained by the server. The server may leverage the metadata database to provide further storage efficiencies by storing certain incremental backup data exclusively within the metadata database. Accordingly, the server may implement a data management configuration as part of a backup service that conserves storage usage, and as a result, storage costs when using on a third-party cloud-based object storage.

Abstract: Described is a system for managing backup data stored on a cloud-based object storage irrespective of the storage provider. The system may include a server (or gateway) that provides a backup service, and acts as an intermediary between a client device and object storage. To provide such capabilities, the system may manage an application programming interface (API) that provides a uniform set of methods to a client device irrespective of the destination object storage provider. A function library may include provider-specific functions that invoke corresponding storage-layer operations provided by the destination object storage. The server may also manage an operation pool to schedule operations and saturate bandwidth to the object storage. The server may also implement a specialized metadata database to provide further storage efficiencies by storing certain backup data exclusively within the metadata database.

Abstract: Item creation in specifically, existing assessment system for institution has lot of malpractices including leakage of question paper, cheating which are of major concern due to manual intervention at multiple levels in lifecycle. This disclosure relates a method to dynamically generate an item by generator function for assessment in candidate console is provided. The method includes one or more templates created for one or more items based on a generator function and one or more placeholder variables. One or more placeholder values are dynamically generated based on one or more replacement values corresponding to each placeholder variable. One or more generated items associated with one or more required options are obtained based on the one or more placeholder values. One or more validated items are obtained by mapping the one or more generated item associated with the one or more required options to the one or more item templates.

Abstract: A system includes a processor configured to perform operations, including determining, for each respective software defect of software defects identified in a software product, corresponding attribute values that represent a software development history of the respective software defect, and determining, for each respective defect, using a machine learning model, and based on the corresponding attribute values, a corresponding escalation value representing a likelihood of the respective defect being escalated for resolution after release of the software product. The machine learning model may have been trained using corresponding software development histories of training defects that were escalated for resolution after release of a prior version of the software product.

Abstract: Described is a system (and method) for providing multiple types of granular delete operations for a cloud-based object storage. The system may include a server that acts as an intermediary between a client device and an object storage that stores client data. The server may allow a client to perform a hard delete (or permanent) delete and a soft delete. The server may perform a specialized processing to synthetically create the soft delete feature using a permanent object delete operation provided by the object storage. The specialized processing may include manipulating retention periods associated with objects depending on whether the object is subject to a hard delete or a soft delete. As a result, the server may provide the ability for clients to perform a soft delete at an object level using existing storage level APIs that do not directly support such a feature.

Abstract: The present invention relates to the beneficial effect of Chebulinic acid (CA) and its enriched standardized fraction (CAEF) isolated/prepared from the fruits of Terminalia chebula for the management of Benign Prostatic Hyperplasia respectively. Further, it relates to a novel, convenient and economically viable method for the isolation of chebulinic acid (CA) and ellagic acid (EA) from the dried and powdered fruits of T. chebula without using any expensive and tedious chromatographic techniques such as HPLC, column chromatography, resins etc.

Abstract: Described is a system for synchronizing expiration times for incremental backup data stored on a cloud-based object storage. More particularly, the system may provide a layer of intelligence when updating the expiration times associated with backup data to ensure that a full recovery of the client data to a point-in-time of any incremental backup may be performed. To provide such a capability, the system may maintain specialized metadata identifying expiration times for objects and a list of objects required to perform a full recovery to a point-in-time for each of the performed backups (e.g. full or incremental). The system may access this metadata to identify which objects stored by a previous backup are still referenced by a subsequent backup. Based on the identified objects, the system may synchronize object expiration times to ensure objects are not prematurely deleted from the object storage.

Abstract: Described is a system for rule-based re-tiering of backup data stored on a cloud-based object storage. More specifically, the system may re-tier objects based on one or more storage rules such that the system retains the ability to efficiently perform a full restore of backup data even when incremental backups are performed to a cloud-based object storage. To provide such a capability, the system may maintain a specialized metadata database that stores information indicating the backup time for each backup, and a list of objects required to perform a full restore to each of the backup times. Accordingly, when initiating a re-tiering based on one or more storage rules, the system may intelligently select candidate objects for re-tiering by leveraging the metadata database to ensure that objects that may still need to be referenced are not unnecessarily moved to a lower storage tier.

Abstract: Described is a system for intelligent re-tiering of backup data stored on a cloud-based object storage. More specifically, the system may re-tier objects such that the system retains the ability to efficiently perform a full restore of backup data even when incremental backups are performed to a cloud-based object storage. To provide such a capability, the system may maintain a specialized metadata database that stores information indicating the backup time for each backup, and a list of objects required to perform a full restore to each of the backup times. Accordingly, when using a threshold time (e.g. expiry) to select object candidates for re-tiering, the system may leverage the metadata database to ensure that objects that may still need to be referenced are not unnecessarily moved to a lower storage tier.

Abstract: Described is a system (and method) for managing specialized metadata that may be used to manage and search incremental backup data stored on a cloud-based object storage. The system may create and store such metadata as part of a specialized metadata database that includes a data catalog and a backup catalog. The system may leverage the metadata database to initiate operations to efficiently manage incremental backup data stored on the object storage. For example, the metadata may be relied upon to efficiently reconstruct (e.g. synthetically) the client data to a point-in-time of any incremental backup. In addition, the metadata may include properties of the backed-up data, which are maintained separately from the backup data stored as objects. Accordingly, these properties may be searched to identify and locate backup data without having to retrieve the stored objects.

Abstract: In some embodiments, described is a system (and method) for providing an efficient preview capability for emails backed up to a cloud-based object storage. The email preview may be provided as part of an interface allowing a user to select individual emails to restore from the object storage. The system may extract specialized preview information as part of a backup procedure. The preview information may include metadata and email content. For example, the preview information may include various email details such as sender, receiver, subject line, time sent/received, filenames of any attachments, etc. The preview information may also include email content such as particular sentences from the email body containing keywords. The system may also store extracted preview information in a specialized manner such that the preview information may be retrieved without having to access the actual backup data.

Abstract: Described is a system for synchronizing expiration times for incremental backup data stored on a cloud-based object storage. More particularly, the system may provide a layer of intelligence when updating the expiration times associated with backup data to ensure that a full recovery of the client data to a point-in-time of any incremental backup may be performed. To provide such a capability, the system may maintain specialized metadata identifying expiration times for objects and a list of objects required to perform a full recovery to a point-in-time for each of the performed backups (e.g. full or incremental). The system may access this metadata to identify which objects stored by a previous backup are still referenced by a subsequent backup. Based on the identified objects, the system may synchronize object expiration times to ensure objects are not prematurely deleted from the object storage.

Abstract: Described is a system that leverages object storage provided access controls to secure backup data stored on a third-party cloud-based object storage. More particularly, the system may implement a mechanism that ensures that a backup system acts as a gateway for accessing the backup data stored on the object storage. For example, the system may prevent object storage administrative accounts that are authorized to access data directly on the storage from maliciously or inadvertently jeopardizing the integrity of the backup data. Moreover, the backup system may encrypt the backup data to prevent such administrative accounts from performing various backup related operations such as data recovery. Accordingly, to perform backup operations and decrypt the backup data, an account must be authorized by the backup system acting as an exclusive gateway to the backup data stored on a third-party storage.

Abstract: Described is a system for intelligent re-tiering of backup data stored on a cloud-based object storage. More specifically, the system may re-tier objects such that the system retains the ability to efficiently perform a full restore of backup data even when incremental backups are performed to a cloud-based object storage. To provide such a capability, the system may maintain a specialized metadata database that stores information indicating the backup time for each backup, and a list of objects required to perform a full restore to each of the backup times. Accordingly, when using a threshold time (e.g. expiry) to select object candidates for re-tiering, the system may leverage the metadata database to ensure that objects that may still need to be referenced are not unnecessarily moved to a lower storage tier.

Abstract: Described is a system for rule-based re-tiering of backup data stored on a cloud-based object storage. More specifically, the system may re-tier objects based on one or more storage rules such that the system retains the ability to efficiently perform a full restore of backup data even when incremental backups are performed to a cloud-based object storage. To provide such a capability, the system may maintain a specialized metadata database that stores information indicating the backup time for each backup, and a list of objects required to perform a full restore to each of the backup times. Accordingly, when initiating a re-tiering based on one or more storage rules, the system may intelligently select candidate objects for re-tiering by leveraging the metadata database to ensure that objects that may still need to be referenced are not unnecessarily moved to a lower storage tier.

Abstract: Described is a system (and method) for managing specialized metadata that may be used to manage and search incremental backup data stored on a cloud-based object storage. The system may create and store such metadata as part of a specialized metadata database that includes a data catalog and a backup catalog. The system may leverage the metadata database to initiate operations to efficiently manage incremental backup data stored on the object storage. For example, the metadata may be relied upon to efficiently reconstruct (e.g. synthetically) the client data to a point-in-time of any incremental backup. In addition, the metadata may include properties of the backed-up data, which are maintained separately from the backup data stored as objects. Accordingly, these properties may be searched to identify and locate backup data without having to retrieve the stored objects.

Abstract: Described is a system for managing backup data stored on a cloud-based object storage irrespective of the storage provider. The system may include a server (or gateway) that provides a backup service, and acts as an intermediary between a client device and object storage. To provide such capabilities, the system may manage an application programming interface (API) that provides a uniform set of methods to a client device irrespective of the destination object storage provider. A function library may include provider-specific functions that invoke corresponding storage-layer operations provided by the destination object storage. The server may also manage an operation pool to schedule operations and saturate bandwidth to the object storage. The server may also implement a specialized metadata database to provide further storage efficiencies by storing certain backup data exclusively within the metadata database.

Abstract: Described is a system (and method) for specialized data management when performing incremental backups to a cloud-based object storage. When backing up client data, the server may utilize incremental backups to conserve the amount of storage space required on the object storage. However, the server may implement a configuration that enables full reconstruction of the client data at the time of recovery. To provide such capabilities, the server may leverage a specialized metadata database. The metadata database may be an embedded database maintained by the server. The server may leverage the metadata database to provide further storage efficiencies by storing certain incremental backup data exclusively within the metadata database. Accordingly, the server may implement a data management configuration as part of a backup service that conserves storage usage, and as a result, storage costs when using on a third-party cloud-based object storage.