This project aims to advance the state of the art by defining an approach that uses machine learning techniques to automate the migration of monolithic software into microservice architecture. The purpose is to aid software engineers in identifying candidate microservices from existing software systems by using features and metrics of the code.
The main research question is “How can we use machine learning techniques to extract microservices from existing software?”
The following sub questions can be defined:
- What are the criteria that need to be analysed in the monolithic to define microservice architectural elements?
- How can we combine efficient machine learning techniques to perform the migration?
- What methodology and tool support can be defined to facilitate practitioners in their migration to microservices?
Successful applicants will be able to demonstrate skills and experience of object-oriented analysis and design, software architecture, microservices, machine learning and familiarity with software repositories such as github. You should also be able to conduct critical background and literature reviews.
You should be highly motivated, able to work independently as well as in a team, collaborate with others and have good communication skills. Project and time management skills are essential.
Doctoral research programmes (PhDs) take a proud place in the world-class research environment and community at Brunel. PhD students are recognised and valued by their supervisors as an essential part of their departments and a key component of the university's overall strategy to develop and deliver world-class research.
A PhD programme is expected to take 3 years full-time or 6 years part-time, with intakes starting in January, April or October.
The general University entrance requirement for registration for a research degree is normally a First or Upper Second Class Honours degree (1st or 2:1) or an international equivalent. A Masters degree is a welcome, but not required, qualification for entry.
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