Bank of America Corporation

Vidhya Vaithiyanathan

Raja Arumugam Maharaja

Sreekanth Raghuveer Maringanti

Shahid Khan Gorewal

Pankaj Kumar

Vijay Singh Shekhawat

Anil Kumar Arora

Aspects of the disclosure relate to intelligently managing invoice processing using blockchain and mixed reality applications. The computing platform may receive invoices and may analyze the invoices to determine a priority order in which the invoices should be processed. The computing platform may use an auto-matching algorithm to identify errors within the invoice and to generate proposed solutions to fix the errors. The computing platform may transmit the invoice to an enterprise organization for modifications and may receive, from the enterprise organization, confidential data including a modified invoice. The computing platform may receive, from an entity associated with a transaction indicated on the invoice, a request to access the modified invoice using a mixed reality application. The computing platform may receive, from the entity and based on the entity's review of the modified invoice using the mixed reality application, approval to execute the modified invoice.

Intelligently managing invoice processing using blockchain and mixed reality applications

A system includes a source code repository which stores source code entries, which include instructions in a programming language for performing computing tasks. A code generator receives an input which includes a request to perform a first computing task. Keywords, including a variable-associated keyword and a function-related keyword, are identified in the input. Code-line entries are determined which, when executed in an ordered combination, achieve the first computing task. Based on the variable-associated keyword, variables appearing in the source code repository are determined to declare in order to perform the first computing task. Based on the function-related keyword, functions appearing in the source code repository are determined to define and call to perform the first computing task. A custom code is generated, in the programming language.

Source code compiler using natural language input

A system includes a source code repository which stores source code entries, which include instructions in a programming language for performing computing tasks. A style repository stores a style profile. Each style profile includes predefined style features associated with formatting characteristics of the stored source code entries. A source code analyzer receives a source code which includes instructions in the programming language for performing a computing task. Style features of the source code are determined. The style features include characteristics of a format of the source code. The source code analyzer determines whether the style features correspond to predefined style features indicated by a style profile. If this is the case, the source code is stored in the source code repository. If this is not the case, storage of the source code is prevented.

System and method for detecting source code anomalies

A system includes a source code repository which stores source code entries, which include instructions in a programming language for performing computing tasks. A style repository stores a style profile for a plurality of users. Each style profile includes predefined style features associated with formatting characteristics of the stored source code entries for a corresponding user. A source code analyzer receives, from a user, a source code which includes instructions in the programming language for performing a computing task. Style features of the source code are determined. The style features include characteristics of a format of the source code. The source code analyzer determines whether the style features correspond to predefined style features indicated by a style profile of the user. If this is the case, the source code is stored in the source code repository. If this is not the case, storage of the source code is prevented.

A system includes a source code repository which stores source code entries, which include instructions in a programming language for performing computing tasks. A code generator receives, from a user, an input which includes a request in a natural language to perform a first computing task. Keywords, including include a variable-associated keyword and a function-related keyword, are identified in the input. Code-line entries, including a variable-declaration, a function-definition, and a function-call entry, are determined which, when executed in an ordered combination, achieve the first computing task. Based on the variable-associated keyword, variables appearing in the source code repository are determined to declare in order to perform the first computing task. Based on the function-associated keyword, functions appearing in the source code repository are determined to define and call to perform the first computing task. A custom code is generated, in the programming language.

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Chennai, India

Vidhya Vaithiyanathan