Abstract: According to examples, development and production data based application evolution may include ascertaining a goal, development data, and production data for a specified release of an application. Development and production data based application evolution may further include determining, from the development data, a feature, a use-case associated with the feature, and a plurality of tasks associated with the use-case. Further, development and production data based application evolution may include determining, from the production data, production log data and user feedback, determining, from the production log data and the user feedback data, criteria, ascertaining, a weightage for each criterion of the criteria, and determining, based on the weightage, a task priority for each task of the plurality of tasks to be applied to a different release of the application.

Abstract: Multi-data analysis based proactive defect detection and resolution may include analyzing operational data for an application to determine whether a functionality related to the application is below a predetermined threshold associated with the functionality related to the application, and based on the analysis, generating an indication to perform defect analysis related to the functionality related to the application. A sentiment analysis may be performed on consumer data related to the application to determine a sentiment of the consumer data related to the application, and a natural language processing (NLP) analysis may be performed on the consumer data related to the application to determine a function associated with a negative sentiment. Application code and process data related to the application may be analyzed to determine a defect associated with the application. Further, a code of the application may be modified to correct the defect associated with the application.

Abstract: According to examples, development and production data based application evolution may include ascertaining a goal, development data, and production data for a specified release of an application. Development and production data based application evolution may further include determining, from the development data, a feature, a use-case associated with the feature, and a plurality of tasks associated with the use-case. Further, development and production data based application evolution may include determining, from the production data, production log data and user feedback, determining, from the production log data and the user feedback data, criteria, ascertaining, a weightage for each criterion of the criteria, and determining, based on the weightage, a task priority for each task of the plurality of tasks to be applied to a different release of the application.

Abstract: Multi-data analysis based proactive defect detection and resolution may include analyzing operational data for an application to determine whether a functionality related to the application is below a predetermined threshold associated with the functionality related to the application, and based on the analysis, generating an indication to perform defect analysis related to the functionality related to the application. A sentiment analysis may be performed on consumer data related to the application to determine a sentiment of the consumer data related to the application, and a natural language processing (NLP) analysis may be performed on the consumer data related to the application to determine a function associated with a negative sentiment. Application code and process data related to the application may be analyzed to determine a defect associated with the application. Further, a code of the application may be modified to correct the defect associated with the application.

Abstract: Multi-data analysis based proactive defect detection and resolution may include analyzing operational data for an application to determine whether a functionality related to the application is below a predetermined threshold associated with the functionality related to the application, and based on the analysis, generating an indication to perform defect analysis related to the functionality related to the application. A sentiment analysis may be performed on consumer data related to the application to determine a sentiment of the consumer data related to the application, and a natural language processing (NLP) analysis may be performed on the consumer data related to the application to determine a function associated with a negative sentiment. Application code and process data related to the application may be analyzed to determine a defect associated with the application. Further, a code of the application may be modified to correct the defect associated with the application.

Abstract: Multi-data analysis based proactive defect detection and resolution may include analyzing operational data for an application to determine whether a functionality related to the application is below a predetermined threshold associated with the functionality related to the application, and based on the analysis, generating an indication to perform defect analysis related to the functionality related to the application. A sentiment analysis may be performed on consumer data related to the application to determine a sentiment of the consumer data related to the application, and a natural language processing (NLP) analysis may be performed on the consumer data related to the application to determine a function associated with a negative sentiment. Application code and process data related to the application may be analyzed to determine a defect associated with the application. Further, a code of the application may be modified to correct the defect associated with the application.

Abstract: The data vaporizer provides secure online distributed data storage services that securely store and retrieve data in a public distributed storage substrate such as public cloud. The data vaporizer vaporizes (e.g., fragmented into tiny chunks of configurable sizes) data and distributes the fragments to multiple storage nodes so that the data is not vulnerable to local disk failures, secures data so that even if some of the storage nodes are compromised, the data is undecipherable to the attacker, stores data across multiple cloud storage providers and/or parties using keys (e.g., tokens) provided by multiple parties (including the owners of the data) and maintains data confidentiality and integrity even where one or more data storage provider is compromised. The data vaporizer is configurable for different domain requirements including data privacy and anonymization requirements, encryption mechanisms, regulatory compliance of storage locations, and backup and recovery constraints.

Abstract: A communication access control system (100) includes at least one access control cell (160), implemented on a computing entity, for computing random input addresses (205) and random output addresses (210) upon a request of a system user (105). The input and output addresses are based on a cryptographic key (165) held by a service facility (115) associated with the at least one access control cell (160).

Abstract: A data shuffling and encryption system may include data storage to store a key and a coding module to shuffle and encrypt an input data sequence. The shuffling and encrypting may include determining an n-dimensional space and populating the n-dimensional space with the input data sequence. A quasi-random function may be applied to sample the n-dimensional space, and samples may be used as an index into the n-dimensional space to determine an output data sequence from the n-dimensional space.

Abstract: A communication access control system includes a messaging service facility and a computing system. The computing system has a permanent memory and hosts a plurality of access control cells (each having an input and an output address); a messaging service to send messages between at least some of the access control cells; and a control service to define a link. The link is selected from a C-link, an F-link, and a Q-link. The C-link connects the output address of a first read-write cell of the access control cells to the input address of a second read-write cell of the access control cells. The F-link connects a forwarder address to the input address of at least one of the access control cells. The Q-link connects the output address of at least one of the access control cells to a queue address.

Abstract: A communication access control system includes a messaging service facility and a computing system. The computing system has a permanent memory and hosts a plurality of access control cells (each having an input and an output address); a messaging service to send messages between at least some of the access control cells; and a control service to define a link. The link is selected from a C-link, an F-link, and a Q-link. The C-link connects the output address of a first read-write cell of the access control cells to the input address of a second read-write cell of the access control cells. The F-link connects a forwarder address to the input address of at least one of the access control cells. The Q-link connects the output address of at least one of the access control cells to a queue address.

Abstract: A data shuffling and encryption system may include data storage to store a key and a coding module to shuffle and encrypt an input data sequence. The shuffling and encrypting may include determining an n-dimensional space and populating the n-dimensional space with the input data sequence. A quasi-random function may be applied to sample the n-dimensional space, and samples may be used as an index into the n-dimensional space to determine an output data sequence from the n-dimensional space.

Abstract: The data vaporizer provides secure online distributed data storage services that securely store and retrieve data in a public distributed storage substrate such as public cloud. The data vaporizer vaporizes (e.g., fragmented into tiny chunks of configurable sizes) data and distributes the fragments to multiple storage nodes so that the data is not vulnerable to local disk failures, secures data so that even if some of the storage nodes are compromised, the data is undecipherable to the attacker, stores data across multiple cloud storage providers and/or parties using keys (e.g., tokens) provided by multiple parties (including the owners of the data) and maintains data confidentiality and integrity even where one or more data storage provider is compromised. The data vaporizer is configurable for different domain requirements including data privacy and anonymization requirements, encryption mechanisms, regulatory compliance of storage locations, and backup and recovery constraints.

Abstract: A communication access control system (100) includes at least one access control cell (160), implemented on a computing entity, for computing random input addresses (205) and random output addresses (210) upon a request of a system user (105). The input and output addresses are based on a cryptographic key (165) held by a service facility (115) associated with the at least one access control cell (160).