Insight into a method co-change pattern to identify highly coupled methods: An empirical study

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dc.contributor.authorMondal, M.
dc.contributor.authorRoy, C.K.
dc.contributor.authorSchneider, K.A.
dc.date.accessioned2015-07-29T19:17:47Z
dc.date.available2015-07-29T19:17:47Z
dc.date.issued2013
dc.description.abstractIn this paper, we describe an empirical study of a unique method co-change pattern that has the potential to pinpoint design deficiency in a software system. We automatically identify this pattern by inspecting the method co-change history using reasonable constraints on method association rules. We also investigate the effect of code clones on the method co-changes identified according to the pattern, because there is a common intuition that clone fragments from the same clone class often require corresponding changes to ensure they remain consistent with each other. According to our in-depth investigation on hundreds of revisions of seven open-source software systems considering three types of clones (Type 1, Type 2, Type 3), our identified pattern helps us detect methods that are logically coupled with multiple other methods and that exhibit a significantly higher modification frequency than other methods. We call the methods detected by the pattern MMCGs (Methods appearing in Multiple Commit Groups) considering the pattern semantic. MMCGs can be considered as the candidates for restructuring in order to minimize coupling as well as to reduce the change-proneness of a software system. According to our observation, code clones have a significant effect on method co-changes as well as on MMCGs. We believe that clone refactoring can help us minimize evolutionary coupling among methods.en_US
dc.description.refereedYesen_US
dc.identifier.doi10.1109/ICPC.2013.6613838
dc.identifier.urihttp://hdl.handle.net/1880/50693
dc.identifier.urihttps://doi.org/10.11575/PRISM/46252
dc.publisherIEEEen_US
dc.publisher.urlhttp://dx.doi.org/10.1109/ICPC.2013.6613838en_US
dc.titleInsight into a method co-change pattern to identify highly coupled methods: An empirical studyen_US
dc.typeunknown
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