Primary supervisor

Yongqiang Tian

This project investigates how user and developer behaviour can be modelled as latent states underlying observable software-engineering and requirements-engineering artefacts, and how recovering these states can deliver actionable insight to practitioners — for example, early signals of requirement instability, indicators of stakeholder misalignment, or behavioural predictors of defect-prone modules.

The project takes an empirical perspective: research questions originate from real problems in software engineering, and are answered through analysis of artefacts produced by developers and stakeholders in practice.

Aim/outline

  • formulate research questions on behavioural and intent-driven phenomena in software engineering
  • propose actionable advice for practitioners 
  • draft an academic paper / Masters thesis

Required knowledge

  • solid foundation in Bayesian statistics and probabilistic modelling
  • familiarity with software engineering artefacts (Git, issue trackers, code review systems) — or willingness to ramp up quickly
  • good data-analysis and written-communication skills
  • genuine interest in empirical research and willingness to commit time to the project
  • exposure to latent state-space or sequential modelling techniques is a plus