Reproducibility Debt in Data Science Software (HDR)



External Member

Dr Zadia Codabux, University of Saskatchewan (Canada)


This project will work in the intersection of datascience/scientific software alongside Technical Debt, to study the reproducibility crisis from a Software Engineering lens/perspective.

You will be conducting systematic literature reviews, mining software repositories, and using mixed-methods.


  • You must hold an Honours Degree First Class
  • Previous experience with programming languages (ideally, both Python and R). Coding and programming is an essential skill for this position.
  • Writing academic papers presented at student conferences.
How to apply:
Please read the instructions on my website, in the section "Graduate's Recruitment":
Note that women and female-identifying candidates are particularly encouraged to apply.

Background Literature

Please, take a look at Dr Vidoni's papers here:



  • Empirical Software Engineering
  • Scientific Software / Data Science Software
  • Technical Debt / Smells
  • Mining Software Repositories
  • Mixed Methods, Developers Surveys

Updated:  10 August 2021/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing