Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.

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 device may obtain text to be analyzed to identify glossary terms. The device may analyze a linguistic unit to generate multiple linguistic units related to the linguistic unit. The device may analyze the multiple linguistic units to generate potential glossary terms. The device may perform a glossary term analysis on the potential glossary terms to generate glossary terms that include a subset of the potential glossary terms. The device may identify included terms that are included in the glossary terms. The device may identify excluded terms that are excluded from the glossary terms. The device may determine a semantic relatedness score between at least one excluded term and at least one included term. The device may selectively add the excluded linguistic term to the glossary terms to form a final set of glossary terms based on the semantic relatedness score, and may output the final set of glossary terms.

Abstract: The REsilient LOosely Coupled (ReLoC) system and method implement a session-state management architecture for cloud computing that uses loosely-coupled services and platform agnostic scalable messaging technology to propagate and save session states. Maintaining the state of applications and user sessions is difficult in large scale web-based software systems, particularly in the context of cloud computing (e.g., platform as a service (PaaS) vendors, do not explicitly support state management infrastructure, such as clustering). In a PaaS environment, a user has little or no access and control over the server platform and session management layer. The platform tiers are generally loosely coupled and service-oriented, which make traditional session-state management techniques non-usable. The ReLoC system and method provides a high level of tolerance to failures of the platform tiers without corresponding disruptions in user sessions.

Abstract: A distribution plan that indicates how to encode and distribute backup data across multiple data centres may be generated. The distribution plan may be generated such that one or more characteristics of the distribution plan, such as costs, are optimized while constraints on the plan, such as protection level, recovery point objective (RPO), and recovery time objective (RTO) are satisfied. The protection level may indicate the number of the data centres that are to remain available such that the backup data is recoverable from encoded fragments of the backup data stored in the data centres that remain available.

Abstract: A method for component discovery from source code may include receiving source code, and determining business classes by excluding packages and classes in the source code identified as belonging to a presentation layer, as belonging to a data access layer, as models and/or as utilities. The method may further include extracting multi-dimensional features from the business classes, estimating similarity for business class pairs based on the extracted multi-dimensional features, clustering the business classes based on the similarity and mapping functional concepts to the clusters. The clusters generated by the clustering may represent components of the source code. The method may also include determining interfaces for the components based on the clustering.

Abstract: A distribution plan that indicates how to encode and distribute backup data across multiple data centres may be generated. The distribution plan may be generated such that one or more characteristics of the distribution plan, such as costs, are optimized while constraints on the plan, such as protection level, recovery point objective (RPO), and recovery time objective (RTO) are satisfied. The protection level may indicate the number of the data centres that are to remain available such that the backup data is recoverable from encoded fragments of the backup data stored in the data centres that remain available.

Abstract: A method for scheduling a plurality of computation jobs to a plurality of data processing units (DPUs) in a grid computing system 100. The method includes receiving a first computation job by a scheduling DPU from the plurality of computation jobs. Further, the method includes scheduling the first computation job at a first set of DPUs in the grid computing system based on first scheduling criteria. Furthermore, the method includes scheduling the first computation job at a first DPU from the first set of DPUs based on second scheduling criteria. The method also includes storing information about the first computation job and the first set of DPUs in a history table at the scheduling DPU. The method further includes storing information about the first DPU in a demand matrix of the first set of DPUs.

Abstract: A requirements testing system facilitates the review and analysis of requirement statements for software applications. The requirements testing system generates test artifacts from the requirement statements. The test artifacts characterize the requirements statements to provide valuable analysis information that aids understanding whether the requirement statements are testable, what the intentions of the requirement statements are, and other useful analysis information. Because the system generates the analysis information from the requirement statements, the system provides benefits in terms of early feedback along the software application development timeline.

Abstract: A system and method for assessing performance of a software application migrated to a grid infrastructure is provided. The system comprises a grid code analyzer for generating a directed acyclic graph (DAG) corresponding to the software application by performing static and dynamic analysis; a grid task generator for reducing the DAG generated by the grid code analyzer; and a grid simulator for simulating performance of the software application on one or more predetermined grid infrastructures. The grid simulator accepts the reduced DAG as input and produces performance data as output.

Abstract: A method for scheduling a plurality of computation jobs to a plurality of data processing units (DPUs) in a grid computing system 100. The method includes receiving a first computation job by a scheduling DPU from the plurality of computation jobs. Further, the method includes scheduling the first computation job at a first set of DPUs in the grid computing system based on first scheduling criteria. Furthermore, the method includes scheduling the first computation job at a first DPU from the first set of DPUs based on second scheduling criteria. The method also includes storing information about the first computation job and the first set of DPUs in a history table at the scheduling DPU. The method further includes storing information about the first DPU in a demand matrix of the first set of DPUs.

Abstract: A system and method for assessing performance of a software application migrated to a grid infrastructure is provided. The system comprises a grid code analyzer for generating a directed acyclic graph (DAG) corresponding to the software application by performing static and dynamic analysis; a grid task generator for reducing the DAG generated by the grid code analyzer; and a grid simulator for simulating performance of the software application on one or more predetermined grid infrastructures. The grid simulator accepts the reduced DAG as input and produces performance data as output.

Abstract: A method of developing early design components of a software application includes identifying business events. An object model or entity relationship diagram is drawn to identify the entities. A matrix is created to evaluate how the business events interact with the entities. Clustering is applied to identify a selected set of entity components (ECs) from the matrix. Process components (PCs) are then created from business events that are not methods of ECs.