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From Christian Schneider <>
Subject Re: Feedback of my Phd work in CXF project
Date Thu, 10 Dec 2015 09:37:43 GMT
The criteria you mention sound a bit academic.

Isn't the real reason of the combined change rather that the classes are 
connected to each other?
I also do not yet get what the use cases for the prediction are.

Of course it is interesting that you can predict such changes but what 
can be done with this information.


On 10.12.2015 00:29, igorwiese wrote:
> Hi, CXF Community.
> My name is Igor Wiese, phd Student from Brazil. I am investigating two
> important questions: What makes two files change together? Can we predict
> when they are going to co-change again?
> I've tried to investigate this question on the CXF project. I've collected
> data from issue reports, discussions and commits and using some machine
> learning techniques to build a prediction model.
> I collected a total of 6384 commits in which a pair of files changed
> together and could correctly predict 86% commits. These were the most useful
> information for predicting co-changes of files:
> - number of lines of code added,
> - number of lines of code removed,
> - sum of number of lines of code added, modified and removed,
> - number of words used to describe and discuss the issues, and
> - number of comments in each issue.
> To illustrate, consider the following example from our analysis. For release
> 2.7, the files "cxf/jaxrs/provider/" and
> "cxf/jaxrs/provider/" changed together in 11
> commits. In another 11 commits, only the first file changed, but not the
> second. Collecting contextual information for each commit made to first file
> in release 2.6, we were able to predict 9 commits in which both files
> changed together in release 2.7, and we only issued one false positive, and
> one wrong prediction. For this pair of files, the most important contextual
> information was the number of lines of code added in each commit, the number
> of lines of code removed in each commit, the sum of lines of code removed,
> added and modified in each commit  and the number of words used to describe
> and discuss the issues.
> - Do these results surprise you? Can you think in any explanation for the
> results?
> - Do you think that our rate of prediction is good enough to be used for
> building tool support for the software community?
> - Do you have any suggestion on what can be done to improve the change
> recommendation?
> You can visit a webpage to inspect the results in details:
> All the best,
> Igor Wiese
> Phd Candidate
> --
> View this message in context:
> Sent from the cxf-dev mailing list archive at

Christian Schneider

Open Source Architect

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