Recommendation Systems in Software EngineeringAlthough software systems control many aspects of our daily life world, no system is perfect. Many of our day to day experiences with computer programs are related to software bugs. And although software bugs are very unpopular, empirical software engineers and software repository analysts rely on bugs or at least on those bugs that get reported to issue management systems. So what makes data software repository analysts appreciate bug reports? Bug reports are development artefacts that relate to code quality and thus allow us to reason about code quality and quality is key to reliability, end-users, success, and finally profit. This chapter serves as a hand-on tutorial how to mine bug reports, relate them to source code, and use the knowledge of bug fix locations to model, estimate, or even predict source code quality. But this chapter also discusses risks that should be addressed before one can achieve reliable recommendation systems.
The book will be available from Springer. For more details and release dates please visit the Springer website under http://www.springer.com/computer/swe/book/978-3-642-45134-8?otherVersion=978-3-642-45135-5

K. Herzig and A. Zeller, “Mining bug data,” in Recommendation systems in software engineering, M. P. Robillard, W. Maalej, R. J. Walker, and T. Zimmermann, Eds., Springer Berlin Heidelberg, 2014, pp. 131-171.
[Bibtex]

@incollection{herzig-mining_bug_data-2013,
year={2014},
isbn={978-3-642-45134-8},
booktitle={Recommendation Systems in Software Engineering},
editor={Robillard, Martin P. and Maalej, Walid and Walker, Robert J. and Zimmermann, Thomas},
doi={10.1007/978-3-642-45135-5_6},
title={Mining Bug Data},
url={http://dx.doi.org/10.1007/978-3-642-45135-5_6},
publisher={Springer Berlin Heidelberg},
author={Herzig, Kim and Zeller, Andreas},
pages={131-171},
language={English},
link={http://wp.me/p2TI1Q-h3}
}

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