July 2016
Beginner to intermediate
408 pages
10h 58m
English
book
Perspectives on Data Science for Software Engineering
by Tim Menzies, Laurie Williams, Thomas Zimmermann
Content preview from Perspectives on Data Science for Software Engineering
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Identifying fault-prone files in large industrial software systems
E. Weyuker; T. Ostrand Mälerdalen University, Västerås, Sweden
Abstract
We provide an overview of a decade-long research program aimed at identifying the most fault-prone files of large industrial software systems. We describe the motivation, approach used and results observed when we applied this technology to 170 releases of 9 different systems running continuously in the field. In all cases the files predicted to be most fault-prone accounted for most of the bugs in the system.
Keywords
Software fault prediction; Fault-proneness; Predictive model; Standard Model; Industrial software
Acknowledgment
This work was supported in part by the Swedish Research Council through ...
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