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Many software developers rely on open source software for developing theirapplications and writing their source codes. Measuring an independent project'soverall productivity is still an open problem for many technology companies. Inthis project, we address to bridge the gap of analyzing which are the mostimportant features for prediction of a productivity based system. We havechosen to collect data from GitHub via their application programming interfaces(API) and analyze the data we gathered to understand the relation between theaverage time to close an issue and the features that we collected. Since mostof the data we gathered were not Gaussian, we had to preprocess the data usingoutlier detection and applying transformations before statistical modeling. Thebest model we observed was polynomial regression with degree 5. Overall, wenoticed that there are many aspects of software development that makedevelopers increase their productivity.

Influence of Communication Among Shared Developers on the Productivity of Open Source Software Projects