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Reproducibility Debt in Data Science Software (HDR)
People
Supervisor
External Member
Dr Zadia Codabux, University of Saskatchewan (Canada)
Description
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.
Requirements
- 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": https://melvidoni.rbind.io/students/
Note that women and female-identifying candidates are particularly encouraged to apply.
Background Literature
Please, take a look at Dr Vidoni's papers here: https://melvidoni.rbind.io/project/2020-rse/
Keywords
- Empirical Software Engineering
- Scientific Software / Data Science Software
- Technical Debt / Smells
- Mining Software Repositories
- Mixed Methods, Developers Surveys
