DocumentCode :
251852
Title :
Examining the relationship between topic model similarity and software maintenance
Author :
Grant, Steven ; Cordy, James R.
Author_Institution :
Sch. of Comput., Queen´s Univ., Kingston, ON, Canada
fYear :
2014
fDate :
3-6 Feb. 2014
Firstpage :
303
Lastpage :
307
Abstract :
Software maintenance is the last phase of software development, and typically one of the most time-consuming. One reason for this is the difficulty in finding related source code fragments. A high-level understanding of the source code is necessary to make decisions about which source code fragments should be modified together, for example, in the context of fixing a bug. Even with a similarity metric available, understanding what it means to measure similarity in the first place is important; if a technique suggests that two source code fragments are related, is there a human-oriented way of explaining that relation? In this paper, we attempt to identify a concrete link between software maintenance and the similarity metrics provided by latent topic models. We show that similarity in topic models is related to the likelihood that source code fragments will be modified together in the future, and that an awareness of similar source code can make software maintenance easier.
Keywords :
data mining; software maintenance; unsupervised learning; bug fixing; latent topic models; similarity measurement; similarity metric; software development; software maintenance; source code fragments; source code understanding; topic model similarity; Context; History; Maintenance engineering; Predictive models; Software maintenance; Software systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Maintenance, Reengineering and Reverse Engineering (CSMR-WCRE), 2014 Software Evolution Week - IEEE Conference on
Conference_Location :
Antwerp
Type :
conf
DOI :
10.1109/CSMR-WCRE.2014.6747182
Filename :
6747182
Link To Document :
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