Bank of America Corporation

Srinath Nelakuditi

Kalyan Chakravarthy Pallapolu

Balamurali Lakshminarayanan

Gali Mohan Sreenivas

Mohana Madhuri Patri

Kiran Kumar Ampabathina

Kalyan Chakravarty Saraswatula

Rahul Devane

Suneetha Padala

R K Kiran Kumar

Phani Raj Gattu

Venkateswar Rao Nerella

Satti Rajeswara Seshareddy

Satya Jonnadula

Mubashshir Ahmed Nazir Ahmed

Systems, computer program products, and methods are described herein for reviewing software code changes in an augmented reality platform. The present invention is configured to receive a request to merge a code change with a main project repository; in response, retrieve metadata associated with the code change; generate a standard compiler output by compiling the metadata associated with the code change; identify one or more objects and one or more layouts from the standard compiler output; retrieve one or more 3D models for the one or more objects; generate an augmented modeling session for display on a first user input device; receive, from the first user input device, a user acknowledgement of the code change; and merge the code change with the project repository.

Three-dimensional software code review engine

Systems, computer program products, and methods are described herein for automated code resolution in an extended reality environment. The present invention allows a user (such as a software developer) to view source code discrepancies in real time using an extended reality (XR) environment. In this regard, the present invention focuses on electronic applications (and the electronic work products/electronic data hosted thereon) and represents a combined view of real-time applications and application requirements within an XR environment. A user may then visualize discrepancies between the current application and the application requirements via an XR platform (accessible using a virtual/augmented/mixed reality device) and proactively make edits, approvals, or otherwise interact with said application. The system may also be configured to automatically alter the source code to resolve said discrepancies.

Extended reality platform and machine learning engine for automated code error resolution

Systems, computer program products, and methods are described herein for reviewing software code changes in an augmented reality platform. The present invention is configured to receive a pull request to merge a code change with a main project repository; in response, retrieve, from a code change repository, metadata associated with the code change; generate a standard compiler output by compiling the metadata associated with the code; identify one or more objects and one or more layouts from the standard compiler output; retrieve one or more 3D models for the one or more objects; generate an augmented modeling session for display on the first user input device; receive, from the first user input device, a user acknowledgement of the code change; and merge the code change with the project repository in response to receiving the user acknowledgement.

An intelligent determination of code change review assignments and subsequent secured access to the determined assignments. Code changes undergo code change complexity determination which is based on (i) a level of importance of the module(s) in which the changes occur, (ii) the volume of metadata files impacted by the code changes, and (iii) the dependency of the code changes on external modules. A distributed trust computing network is implemented and a code change smart contract which relies on smart contract rules is used to determine and allocate code change review assignments. In this regard, data blocks within a distributed ledger define individual segments/portions of the code change file with each data block identifying a code change review assignment.

Secured code assignment and review engine

An apparatus includes a memory and a hardware processor. The memory stores a plurality of previous software errors and a plurality of solutions to the plurality of previous software errors. The processor receives a video of a user describing an error in a software application and tracks a facial feature of the user to determine an emotional intensity. The processor converts an audio portion of the video to a text file and analyzes the text file to determine the error. In response to the emotional intensity exceeding a threshold, the processor determines, based on the plurality of previous software errors, a series of steps that, when performed, replicate the error, determines, based on the series of steps and the plurality of solutions, a change to the source code of the application that fixes the error, and implements the change to the software code.

Error repair tool using sentiment analysis

A code merging system is configured to manage the storage of source code on a local system in the software development cycle. A cloud environment hosts working source code, which is composed of metadata artifact components. Copies of some of the metadata artifact components are transferred to a source code control and merged with master source code in either a partial merge process or a full merge process.

Dynamically updating source code from a cloud environment

Systems, apparatus and methods for intelligent deployment(s) of application objects are provided. The systems, apparatus and methods may include one or more dynamic parameters retrieved from metadata table(s). The parameter(s) may be used to calibrate the deployment(s). The parameter(s) may be associated with previous failed deployment(s). Calibration may be automatic. Calibration may include email sending and/or email previewing components. A testing environment may be used prior to actual deployment.

Dynamic cloud deployment and calibration tool

A smart transmission system is configured to upload data from a plurality of sources to a target application hosted in a cloud environment. A server receives a data stream from the plurality of sources. Using a priority algorithm, the server analyzes the data stream to determine which files and accounts are most critical for the target application's function. The files and their associated accounts are partitioned into tranches, and the tranches are uploaded to the target application in order of priority.

Data transmission using smart clusters

A method comprises receiving a first request from a source, the first request comprising an identification of a first person, a source of the first request, and an indicator whether the first person is currently available for communication. The method further comprises assigning a weight to each of the identification of the person, the source, and the indicator whether the first person is currently available for communication, wherein the assigned weights are based on historical data about the first person and summing each of the assigned weights to produce a prioritization factor. The method further comprises sending the first request to a first telephone dialer if the prioritization factor for the first request is above or equal to a threshold and sending the first request to a second telephone dialer if the prioritization factor for the first request is below the threshold.

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Hyderabad Telangana, India

Srinath Nelakuditi