Amazon Technologies, Inc.

Mark Fawaz

Jiangtao Zhang

Gunja Agrawal

Vivek Chawda

Ramu Panayappan

Abdul Jabbar Abdul Rasheed

Javier Arturo Thiele-Ruiz

Pranav Prabhakar Firake

Kanishk Kaul

Donghao Wei

Sreenaath Vasudevan

Emery Jacob Comstock

Techniques are described for assisting users with the process of modernizing software applications from a source software architectural pattern (e.g., a model—view—controller (MVC) pattern, a multitier architecture, etc.) to a target architectural pattern (e.g., microservices, event-driven architecture, etc.). A decomposition analyzer receives as input artifacts associated with a software application under analysis and an architectural pattern that a user desires to use for a modernized version of the software application. The decomposition analyzer generates, based on the application artifacts, a graph-based model of the software application, where the model includes nodes representing application components (e.g., classes) and edges representing dependency relationships among the components. The decomposition analyzer further uses machine learning techniques and other types of analyses to identify recommended groupings of nodes from the graph-based model for decomposition. These recommendations can be displayed to users in a visualization providing decomposition assessment information.

Guided modernization of software applications using application templates

Techniques are described for enabling the automatic refactoring of software application source code to mitigate identified anti-patterns and other software modernization-related issues. A software modernization system analyzes software applications to generate various types of modernization report information, where the report information can include identifications of various types of design and cloud anti-patterns, proposed decompositions of monolithic applications into subunits, refactoring cost information, recommended modernization tools and migration paths, among other such information. A software modernization system further includes a refactoring engine that can automatically refactor source code based on such application analysis information, e.g., to automatically address identified anti-patterns, restructure code for decomposition, etc. A refactoring engine performs refactoring actions based on refactoring templates, machine learning (ML) refactoring models, or other input.

Automatic source code refactoring to mitigate anti-patterns

Machine learning assisted source code refactoring to mitigate anti-patterns

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Laguna Hills, CA, United States of America

Mark Fawaz