An even more blatant case of plagiarism of our Bayesian Networks work

Spot the difference in our article plagiarised by Daniel and Etuk

Last year I reported the blatant case of plagiarism whereby one of our papers was 'rewritten' by Milan Tuba and Dusan Bulatovic and published in the Journal WSEAS Transactions on Computers. At least Tuba and Bulatovic made an attempt to cover up the plagiarism by inserting our work into a paper with a very different title and with some additional material.

In the latest case (discovered thanks to a tip-off by Emilia Mendes) the 'authors' Matthias Daniel and Ette Harrison Etuk  of Dept. Mathematics and Computer Science, Rivers State University of Science and Technology, Nigeria  have made no such attempt to cover up their plagiarism except to rearrange the words in the title and in a small number of other places. So, for example "reliability and defects" has been replaced by "defects and reliability" at the end of the abstract. The only other difference is that our Acknowledgements have been removed.

Here is the full pdf of our published original paper whose full title and reference is:
Fenton, N.E., Neil, M., and Marquez, D., "Using Bayesian Networks to Predict Software Defects and Reliability". Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, 2008. 222(O4): p. 701-712, 10.1243/1748006XJRR161: 

Here is the full pdf of the plagiarised paper whose full title and reference is: Matthias Daniel, Ette Harrison Etuk, "Predicting Software Reliability and Defects Using Bayesian Networks", European Journal of Computer Science and Information Technology Vol.2, No.1, pp.30-44, March 2014

What is really worrying is that Emilia came across the 'new' paper when doing some google searches on using BNs for defect prediction; it was one of the top ones listed!!!
We are waiting for a response from the European Journal of Computer Science and Information Technology.

Incidentally, the new third edition of my book Software Metrics: A Rigorous and Practical Approach has just been published and (for the first time) it covers the use of Bayesian networks for software reliability and defect prediction.