Enhancing Software Refactoring in the Sri Lankan Software Development Industry through Machine Learning Techniques:Challenges, and Intentions.

Sammanfattning

Software refactoring is a crucial approach in both development and maintenance to improve the efficiency, maintainability, and structure of software systems. However, a number of challenges remain in the way of the effective implementation of software refactoring techniques within Sri Lanka's software development industry. This thesis investigates the challenger in software refactoring process in Sri Lanka software development companies and examine the intentions of developers, software test automation engineer and project managers on the usage on the machine learning techniques for software refactoring and the study uses the Unified Theory of Acceptance and usage of Technology 2 (UTAUT2) extended model. The study demonstrates that professional in software development Industry have positive intentions toward the usage of machine learning techniques, motivated by benefits they perceive, such as increased productivity, maintenance, and improved code quality. This study advances our understanding of software refactoring and theadoption of new ML technologies and offers insightful information to researchers, practitioners, and decision- makers in the Sri Lankan IT sector and beyond.