DocumentCode
2932126
Title
Software-Change Prediction: Estimated+Actual
Author
Kagdi, Huzefa ; Maletic, Jonathan I.
Author_Institution
Dept. of Comput. Sci., Kent State Univ., OH
fYear
2006
fDate
24-24 Sept. 2006
Firstpage
38
Lastpage
43
Abstract
The authors advocate that combining the estimated change sets computed from impact analysis techniques with the actual change sets that can be recovered from version histories will result in improved software-change prediction. An overview of both impact analysis (IA) and mining software repositories (MSR) is given. These are compared and a discussion of their expressiveness and effectiveness is presented. A framework is proposed to integrate these two approaches for software-change prediction
Keywords
configuration management; data mining; software maintenance; software prototyping; actual change sets; impact analysis; mining software repositories; software-change prediction; Computer science; Conferences; History; Information analysis; Performance analysis; Retirement; Software maintenance; Software systems; State estimation; Unified modeling language;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Evolvability, 2006. SE '06. Second International IEEE Workshop on
Conference_Location
Philadelphia, PA
Print_ISBN
0-7695-2698-5
Type
conf
DOI
10.1109/SOFTWARE-EVOLVABILITY.2006.14
Filename
4032446
Link To Document