DocumentCode :
3141866
Title :
Does bug prediction support human developers? Findings from a Google case study
Author :
Lewis, Carmen ; Zhongpeng Lin ; Sadowski, Caitlin ; Xiaoyan Zhu ; Rong Ou ; Whitehead, E. James
Author_Institution :
Univ. of California, Santa Cruz, Santa Cruz, CA, USA
fYear :
2013
fDate :
18-26 May 2013
Firstpage :
372
Lastpage :
381
Abstract :
While many bug prediction algorithms have been developed by academia, they´re often only tested and verified in the lab using automated means. We do not have a strong idea about whether such algorithms are useful to guide human developers. We deployed a bug prediction algorithm across Google, and found no identifiable change in developer behavior. Using our experience, we provide several characteristics that bug prediction algorithms need to meet in order to be accepted by human developers and truly change how developers evaluate their code.
Keywords :
prediction theory; program debugging; software engineering; Google; bug prediction algorithms; developer behavior; human developers; Algorithm design and analysis; Computer bugs; Google; Measurement; Prediction algorithms; Software; Software algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (ICSE), 2013 35th International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4673-3073-2
Type :
conf
DOI :
10.1109/ICSE.2013.6606583
Filename :
6606583
Link To Document :
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