Morgan Stanley Services Group Inc.

Kumar Vadaparty

Vishal Agrawal

Arun Maroli

David Testa

Vilas Mhatre

Thomas Mathew

Martin Leduc

Kallol Duttagupta

Kundan Sen

Alex Suprun

Bhupen Kinariwala

Alberto Ramos

Judith Christi Joy

Abhishek Soni

Bijaya Kumar Pradhan

Shwetank Nagar

Vivek S Agrawal

Freddy Reyes

Trevor Brosnan

Marcelo Leifert

Darryl Alan Sansbury

Velliangiri Karuppusamy

Piyush Aggarwal

A computer-implemented method and system standardize code patterns within enterprise software environments. A code modernization system utilizes a Large Language Model (LLM) and a specialized prompt library. The library includes pattern recognition prompts to guide the LLM in identifying specific code patterns within selected software code, potentially using enterprise-specific context. It also includes standardized solution prompts to guide the LLM in generating replacement code conforming to predefined enterprise standards for the identified patterns. The system orchestrates communication, transmitting code and relevant prompts to the LLM and receiving identified patterns and subsequently the generated standardized replacement code. This automated approach facilitates improved code quality, consistency, maintainability, and can support code translation efforts within the enterprise.

Standardizing enterprise software code through LLMs

A computer-implemented system analyzes program and data flows in a software system comprising code written in multiple programming languages using a generative large language model (LLM) directed by programming-language-specific prompts. The LLM identifies functional components within the code, generating labeled graph nodes that include a node type, a node name, and dependency information. A graph construction computer system processes the labeled graph nodes to generate a directed graph, where nodes represent functional components and directed edges represent dependencies. The system stores the graph in a database and provides a web-based interface for visualization, allowing users to explore, query, and analyze program and data flows across the software system. The system enables automated, language-agnostic dependency mapping, facilitating software analysis, debugging, and modernization.

Multi-language program and data flow analysis using LLM

Computer-implemented systems and methods use a Large Language Model (LLM) for converting a legacy computer program in a first language to a human-language description of the legacy computer program, which description can be validated as being an accurate description of the legacy computer program. Once validated, the human-language description can be converted, again using an LLM, to a computer program in a target programming language. An LLM can also be used to generate test scripts for the new target-language program to test the performance of the target-language program in a production environment. An LLM can also be used to reconcile outputs from the legacy program to the new target program, such as on a function-by-function basis. If the differences between the outputs (if any) are sufficiently negligible, the legacy computer program can be decommissioned, and the new, target language program can be used in production.

Generating new software code from legacy software code using large language models

A method and system of managing incidents in a system by employing preemptive incident prevention and self-healing processing. The method detects potential incidents and actual incidents in the system and performs self-healing prevention actions for any detected potential incidents and performs self-healing actions for any detected or notified incidents. The system performs an automated root cause analysis for event notifications related to an incident.

Methods and systems of incident management employing preemptive incident prevention and self healing processing

An order management system comprises a middle tier and a computer-based automatic rule code generation system. The middle tier comprises a state transition engine that manages rule-based state transitions of trade orders for financial products from one state to a next state in progressions of the trade orders. The computer-based automatic rule code generation system: (i) receives a human-readable state transition file that specifies one or more state transition rules and a corresponding condition for each of the one or more state transition rules; and (ii) generates, at compile time, a configuration file that comprises rule code for the one or more state transition rules from the state transition file. The state transition engine runs the rule code in the configuration file at runtime to manage the state transitions for the trade orders.

Meta data driven state transition engine for order management system

Computer systems and methods test applications of an enterprise computer system. The enterprise computer system comprises a test orchestration engine that is configured to receive a human-readable configuration file that comprises: a test script model that specifies testing activities for an application of the enterprise computer system; an application model that specifies attribute values for the application for the testing of the application; and a script model that specifies context parameters for the testing of the application. The test orchestration engine generates, at compile time, metadata code artifacts from the configuration file; and orchestrate, at run time, testing of the application based on the metadata code artifacts generated from the configuration file.

Multi-role, multi-user, multi-technology, configuration-driven requirements, coverage and testing automation

An efficient reusable, extensible light weight framework statelessly orchestrates system activities in any application which involves a series of sequential or parallel set of activities involving computational logic, data retrieval and persistence services. Actual orchestration steps and activities and computational logic are specified into configuration files, separate from the orchestration engine itself, thereby eliminating the need to code for such logic and activities. The framework can eliminate the need to code business logic and orchestration of data retrieval services by externalizing them into configuration files, resulting in lower costs to implement, test and maintain such system during its lifespan.

Metadata driven orchestration engine

A computer-implemented system and method to track a transaction that is executed by a series of applications in a workflow. Each application in the workflow generates an application log file that includes a standard header, which in turn includes a transaction ID associated with the transaction, an outcome associated with a step of the transaction executed by each of the applications, and a timestamp associated with the step of the transaction. The application log file with the header is received and stored by the computer system. The computer system can thereafter retrieve and display the entire transaction history for the transaction across all of the applications in response to a user query. The standard header is appended to the application log file and agnostic to the underlying technology used to implement the application system so that any transaction can be reconstructed end-to-end regardless of the form of the application system.

System for tracking transaction data across applications

Efficient, reusable, extensible light weight framework orchestrates discrete mainframe service calls as a single composite service call. The single composite call requires a single mainframe socket and the mainframe disaggregates the composite service call upon receipt to process the individual service calls therein, thereby allowing the mainframe to handle more services calls simultaneously. A similar framework orchestrates distributed service calls from a mainframe client.

Mainframe service request orchestrator and multiplexer

An efficient, light weight framework executes business rules for an asset class-agnostic order management system. The business rules are specified in metadata configuration files separated from the rules execution engine. The metadata utilized by the rules engine also includes entity model and instructions for stateless orchestration to be performed during the process of rules execution. This metadata is automatically generated from human readable artifacts that capture business rules, entity model and orchestration steps in an easy to understand format.

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Belle Mead, NJ, United States of America

Kumar Vadaparty