A huge amount of historical information about the evolution of a software project is available in software repositories, namely bug repositories, source control repositories, archived communications, deployment logs, and code repositories. By mining the evolutionary history of a software, we have designed prediction models to assist software developers by predicting bug attributes like priority, severity, assignee and fix time. We have evaluated the uncertainty in the software in terms of entropy arises due to source code changes done in files of the software to fix different issues. To support software managers, we have designed prediction models to predict potential values of entropy and different issues, namely bugs, improvements in existing features (IMPs) and new features (NFs) over a long run. In this research work, we have developed mathematical models to assist software managers and developers in bug triag-ing, bug fixing and different software maintenance related tasks. Our work has been validated on issue and code change data of several open source projects, namely Eclipse, Open office, Mozilla and Apache.
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