Bachelor and Master Theses

Title: Design and implementation of an Eclipse plug-in for software fault prediction
Subject: Computer Science
Level: Advanced
Description: The goal of software fault prediction is to help software engineers focus testing and refactoring activities on fault-prone code, thus improving software quality. There are many software fault prediction studies in software engineering literature, see e.g. recent literature review papers on the topic [1] [2]. However to promote practical usage of software fault prediction, this thesis aims to design and develop an Eclipse plug-in that shall provide an easy, automated and integrated mechanism for software engineers to see whether certain files or classes are fault-prone or not. It is expected that the plug-in will also provide one or more simple prediction methods to achieve fault prediction, besides mechanisms for collection of data and performance evaluation of prediction models. The thesis shall validate the implemented plug-in with other stand-alone tools for software fault prediction, such as WEKA.

Expected outcomes:
1. Design and implementation of Eclipse plug-in for software fault prediction.
2. Comparison and validation of plug-in results with stand-alone tools for software fault prediction.

References:
[1] Hall, T.; Beecham, S.; Bowes, D.; Gray, D.; Counsell, S., "A Systematic Literature Review on Fault Prediction Performance in Software Engineering," in Software Engineering, IEEE Transactions on , vol.38, no.6, pp.1276-1304, Nov.-Dec. 2012.

[2] Ruchika Malhotra, A systematic review of machine learning techniques for software fault prediction, Applied Soft Computing, Volume 27, February 2015, Pages 504-518, ISSN 1568-4946, http://dx.doi.org/10.1016/j.asoc.2014.11.023.
Proposed: 2016-10-31
Prerequisites: 1) Java 2) Eclipse IDE 3) Research methods
IDT supervisor: Wasif Afzal
wasif.afzal@mdh.se,
Examinator:

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