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