Title :
Software-Change Prediction: Estimated+Actual
Author :
Kagdi, Huzefa ; Maletic, Jonathan I.
Author_Institution :
Dept. of Comput. Sci., Kent State Univ., OH
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;
Conference_Titel :
Software Evolvability, 2006. SE '06. Second International IEEE Workshop on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7695-2698-5
DOI :
10.1109/SOFTWARE-EVOLVABILITY.2006.14