Bank of America Corporation

Kumaresan Karuppiah

Samson Paulraj

Vinay Jaisinghani

Ravi Ranjan Shandilya

Obi Reddy Yanamala

Seshidhar R Ammasani

Aspects of this disclosure relate to a blockchain system for management of scripts associated with software applications. The blockchain system may be supplemented by an artificial intelligence (AI)-based system for generation of test scripts. The blockchain system may employ smart contracts for submission and validation of scripts by different nodes of a peer-to-peer (P2P) network.

Blockchain system for source code testing and script generation with artificial intelligence

A system is provided for secure verification of authentication data using quantum computing and a distributed server network. In particular, the system may store a reference set of authentication data associated with a user within a distributed server database in an encrypted form. Subsequently, when the system receives live set of authentication data associated with the user, the system may, using a quantum authenticator, compare the encrypted live set of authentication data with the encrypted reference set of authentication data for authorization purposes. The system may further comprise a quantum machine learning authorization engine which may track historical data and/or settings associated with the user to model and predict behavior patterns of the user. In this way, the system provides a secure and efficient way to perform authentication and/or authorization of the user.

System for secure verification of authentication data using quantum computing and a distributed server network

A system for analyzing the runtime impact of data files on data extraction, transformation, and loading (ETL) jobs typically includes a processor, a memory, and a runtime impact analysis module stored in the memory. The runtime impact analysis module is typically configured for: receiving a user input comprising a designator of a data repository from a user; receiving an ETL job list file from one or more ETL servers; for each ETL job invocation name in the ETL job list file: querying the one or more ETL servers for runtime information, receiving the runtime information from the one or more ETL servers, searching the runtime information for the designator of the data repository, and if the designator of the data repository is identified in the runtime information, adding the ETL job invocation name to an impacted ETL job file; and providing the impacted ETL job file to the user.

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Chennai, India

Kumaresan Karuppiah