Title :
Predicting Eclipse Bug Lifetimes
Author :
Panjer, Lucas D.
Author_Institution :
Univ. of Victoria, Victoria
Abstract :
In non-trivial software development projects planning and allocation of resources is an important and difficult task. Estimation of work time to fix a bug is commonly used to support this process. This research explores the viability of using data mining tools to predict the time to fix a bug given only the basic information known at the beginning of a bug´s lifetime. To address this question, a historical portion of the Eclipse Bugzilla database is used for modeling and predicting bug lifetimes. A bug history transformation process is described and several data mining models are built and tested. Interesting behaviours derived from the models are documented. The models can correctly predict up to 34.9% of the bugs into a discretized log scaled lifetime class.
Keywords :
data mining; database management systems; program debugging; resource allocation; software engineering; data mining model; eclipse Bugzilla database; eclipse bug lifetime; resource allocation; software development project planning; Computer bugs; Computer science; Data mining; Databases; History; Open source software; Predictive models; Programming; Testing; XML;
Conference_Titel :
Mining Software Repositories, 2007. ICSE Workshops MSR '07. Fourth International Workshop on
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-7695-2950-X
DOI :
10.1109/MSR.2007.25
