Hi, Hive Community. My name is Igor Wiese, phd Student from Brazil. I sent an email a week ago about my research. We received some visit to inspect the results but any feedback was provided.
I am investigating two important questions: What makes two files change together? Can we predict when they are going to co-change again? 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 Hive 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 721 commits in which a pair of files changed together and could correctly predict 53% 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 effective size, a social network measure obtained from issue comments. To illustrate, consider the following example from our analysis. For release 0.14, the files "metastore/MetaStoreDirectSql.java" and "metastore/ObjectStore.java" changed together in 4 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 previous release, we were able to predict 4 commits in which both files changed together in release 0.14, and we issued 0 false positives and two wrong predictions. For this pair of files, the most important contextual information was the number of lines of codes added, the sum of lines of codes added, removed and modified, and two social network metrics (constraint, ties) obtained from issue comments - 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: http://flosscoach.com/index.php/17-cochanges/72-hive All the best, Igor Wiese Phd Candidate -- ================================= Igor Scaliante Wiese PhD Candidate - Computer Science @ IME/USP Faculty in Dept. of Computing at Universidade Tecnológica Federal do Paraná
