Mining question and answer (QA) websites to support software practitioners to improve the software development process

   Faculty of Natural Sciences

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  Dr Sangeeta Sangeeta  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Software engineering and data analytics is an active and important research area with many opportunities for innovation.  This project will provide an opportunity to pursue research in the area of data science and software engineering. Software development is a complex process it involves several steps and various stakeholders. The project will work towards automating various software engineering development tasks that can make the software development process efficient. We are particularly interested in analysing content on technical QA websites like Stackoverflow.

The PhD will focus on several important questions related to the QA website. For example, the evolution of the Python community over the period, the problem associated with question migration and early prediction of migrated questions, mining rule violation in Python code etc.

The dataset of Stackoverflow is open source and can be downloaded from the website (Note: we need to pre-process the data according to our requirement):

As well as technical research and development, the PhD would be required to consider ethical considerations in data collection and potential biases in the subsequent analyses.

Related subject areas: Data Science, Data Visualisation, Text mining, Machine Learning, Software engineering

Candidate profile:


Applications are welcomed from computer science/data science graduates with (or anticipating) at least a 2.1 honours degree or equivalent. Applicants will require good general computing skills but will not require specific expertise in software engineering or machine learning.

Applicants should have enthusiasm and a willingness to acquire new skills. Ideally, applicants will be self-motivated and can work both independently and as part of a team.

 This opportunity is open to UK/EU and overseas students. The collaborative and presentation aspects of the research require good English language and communication skills. Overseas applicants would therefore require an English IELTS (or equivalent) of 6.0 overall with no less than5.5 in any subtest.

Applicants should be self-motivated and enjoy working both independently and as part of a team.

To submit a formal application please go to

Please quote FNS 2021-15 on your application

Keele University values diversity, and is committed to ensuring equality of opportunity. In support of these commitments, Keele University particularly welcomes applications from women and from individuals of black and ethnic minority backgrounds for this post. The School of Computing and Mathematics and Keele University have both been awarded Athena Swan awards and Keele University is a member of the Disability Confident scheme. More information is available on these web pages:

Computer Science (8)

Funding Notes

Self funded.


Some links to related publication: