An Empirical Study for the Impact of Maintenance Activities in Clone Evolution

dc.contributor.authorMarks, Lionelen
dc.contributor.departmentComputingen
dc.contributor.supervisorZou, Yingen
dc.date2009-11-25 14:18:05.884
dc.date.accessioned2009-11-26T23:05:02Z
dc.date.available2009-11-26T23:05:02Z
dc.date.issued2009-11-26T23:05:02Z
dc.degree.grantorQueen's University at Kingstonen
dc.descriptionThesis (Master, Computing) -- Queen's University, 2009-11-25 14:18:05.884en
dc.description.abstractCode clones are duplicated code fragments that are copied to re-use functionality and speed up development. However, due to the duplicate nature of code clones, inconsistent updates can lead to bugs in the software system. Existing research investigates the inconsistent updates through analysis of the updates to code clones and the bug fixes used to fix the inconsistent updates. We extend the work by investigating other factors that affect clone evolution, such as the number of developers. On two levels of analysis, the method and clone class level, we conduct an empirical study on clone evolution. We analyze the factors affecting bug fixes and co-change (i.e. update cloned methods at the same time) using our new metrics. Our metrics are related to the developers, code complexity, and stages of development. We use these metrics to find ways to improve the maintenance of cloned code. We discover that one way to improve maintenance of code clones is the decrease of code complexity. We find that increased code complexity leads to a decrease in co-change, which can lead to bugs in the software. We perform our study on 6 applications. To maximize the number of clones detected, we use two existing code clone detection tools: SimScan and Simian. SimScan was used to find clones in 5 of the applications due to its versatility in finding code clones. Simian was used to detect clones due to its reliability to find code clones regardless of language or compilation problems. To analyze and determine the significance of the metrics, we use the R Statistical Toolkit.en
dc.description.degreeM.Sc.en
dc.format.extent1055138 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1974/5336
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectClone Detectionen
dc.subjectClone Evolutionen
dc.titleAn Empirical Study for the Impact of Maintenance Activities in Clone Evolutionen
dc.typethesisen
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Marks_Lionel_200911_MSc.pdf
Size:
1.01 MB
Format:
Adobe Portable Document Format