Novel techniques to refactor software systems using reinforcement learning

Refactoring is an important software development activity that employs various techniques to enhance the structure and quality of source code without altering its functionality. Over the last two decades, researchers in the field have proposed several tools and techniques to enable automated refactoring. Despite a plethora of literature, though some steps can be automated, overall refactoring remains a manual process. In this project, we aim to develop a method to generate refactored code from any given code to improve its maintainability using reinforcement learning.

Faculty Supervisor:

Tushar Sharma

Student:

Partner:

École nationale supérieure d'informatique

Discipline:

Computer science

Sector:

Artificial Intelligence

University:

Dalhousie University

Program:

Globalink Research Award

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