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As Data Mining for Secure Software Engineering improves software productivity and quality, software engineers are increasingly applying data mining algorithms to various software engineering tasks. However mining software engineering data poses several challenges, requiring various algorithms to effectively mine sequences, graphs and text from such data. Software engineering data includes code bases, execution traces, historical code changes, mailing lists and bug data bases. They contains a wealth of information about a projects-status, progress and evolution. Using well established data mining techniques, practitioners and researchers can explore the potential of this valuable data in order to better manage their projects and do produce higher-quality software systems that are delivered on time and with in budget.
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