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Software Quality Improvement (SEQUIN): Proposing a solution to the problem of low data quality in software repositories.

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  • Full or part time
    Prof Harrison
  • Application Deadline
    Applications accepted all year round

Project Description

Come and join our thriving community of research students in our new purpose-built research laboratory.

The aim of this research is to propose a solution to the problem of low data quality in software repositories.

The objectives of the PhD are to:
1. analyse and categorise existing data from open source projects and their quality
2. analyse data pre-processing techniques for software project data 3. develop new software tools and techniques for data pre-processing 4. evaluate the effectiveness and efficiency of the new tools and techniques.

A systematic mapping study will be performed as well as experiments using open source software. This will be followed by software development and validation. A probabilistic approach (Bayesian Belief Network) or simulation (Monte-carlo) may be used. The experimental work will be validated by triangulation.

The Applied Software Engineering Research Group is part of the Department of Computing in the Faculty of Technology, Design and Environment. The Department provides undergraduate and postgraduate degrees in Computer Science and related disciplines. Details about the Department can be found at http://cct.brookes.ac.uk/
We are looking for enthusiastic candidates with:
• a solid background in Computer Science, shown by a good BSc: 2.1 or above and/or an MSc degree;
• a solid background in Mathematics; knowledge of software engineering methods;
• an appreciation of empirical techniques; • good communication and collaboration skills.

As research deliverables we expect publications, software, and a PhD thesis.

If you have any queries about this project, please contact: Rachel Harrison: [email protected] There is more information about our research at http://cct.brookes.ac.uk/research/index.html
For details on how to apply and for details of the likely costs, please contact [email protected]

Funding Notes

There is no funding attached to this project, it is for self-funded students only.

References

Liebchen, G. and Shepperd, M. (2008) 'Data sets and data quality in software engineering', PROMISE 2008 D. Rodriguez, I. Herraiz, R. Harrison, J. Dolado and J. C. Riquelme, Comparison of Techniques for Dealing with Imbalance in Software Defect Prediction, 18th International Conference on Evaluation and Assessment in Software Engineering (EASE), London, May 2014 Khoshgoftaar, Taghi M., and Naeem Seliya. "The necessity of assuring quality in software measurement data." Software Metrics, 2004. Proceedings. 10th International Symposium on. IEEE, 2004.

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