DocumentCode
2745567
Title
Predicting Faults from Cached History
Author
Kim, Sunghun ; Zimmermann, Thomas ; Whitehead, E. James ; Zeller, Andreas
Author_Institution
Massachusetts Inst. of Technol., Cambridge, MA
fYear
2007
fDate
20-26 May 2007
Firstpage
489
Lastpage
498
Abstract
We analyze the version history of 7 software systems to predict the most fault prone entities and files. The basic assumption is that faults do not occur in isolation, but rather in bursts of several related faults. Therefore, we cache locations that are likely to have faults: starting from the location of a known (fixed) fault, we cache the location itself, any locations changed together with the fault, recently added locations, and recently changed locations. By consulting the cache at the moment a fault is fixed, a developer can detect likely fault-prone locations. This is useful for prioritizing verification and validation resources on the most fault prone files or entities. In our evaluation of seven open source projects with more than 200,000 revisions, the cache selects 10% of the source code files; these files account for 73%-95% of faults - a significant advance beyond the state of the art.
Keywords
cache storage; software fault tolerance; 7 software system version history; cache history; fault-prone location prediction; resource validation; resource verification; Fault detection; Fault diagnosis; History; Isolation technology; Open source software; Prediction algorithms; Software algorithms; Software quality; Software systems; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, 2007. ICSE 2007. 29th International Conference on
Conference_Location
Minneapolis, MN
ISSN
0270-5257
Print_ISBN
0-7695-2828-7
Type
conf
DOI
10.1109/ICSE.2007.66
Filename
4222610
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