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From Igor Wiese <>
Subject Feedback of my Phd work in Cloudstack Project
Date Wed, 09 Dec 2015 23:31:26 GMT
Hi, Cloudstack Community.

My name is Igor Wiese, phd Student from Brazil. In my research, 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 Cloudstack 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 141 commits in which a pair of files changed
together and could correctly predict 60% commits. These were the most
useful information for predicting co-changes of files:

- sum of number of lines of code added, modified and removed,

- number of words used to describe and discuss the issues,

- number of comments in each issue,

- median value of closeness, a social network measure obtained from issue
comments, and

- median value of constraint, a social network measure obtained from issue

To illustrate, consider the following example from our analysis. For
release 4.4, the files "cloud/hypervisor/" and
"cloud/hypervisor/guru/ " changed together in 3 commits. In
another 2 commits, only the first file changed, but not the second.
Collecting contextual information for each commit made to first file in the
previous release (4.3), we were able to predict all 3 commits in which both
files changed together in release 4.4, and we only issued 0 false
positives. For this pair of files, the most important contextual
information was the number of lines of code added, removed and modified in
each commit,the number of comments in each issue, and social network
measures (closeness, density, constraint, hierarchy) obtained from issue

- Do these results surprise you? Can you think in any explanation for the

- 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

You can visit our webpage to inspect the results in details:

All the best,
Igor Wiese
Phd Candidate

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