@article {1401,
	title = {Clones: what is that smell?},
	journal = {Empirical Software Engineering},
	volume = {17},
	year = {2012},
	month = {8/2012},
	pages = {503 - 530},
	abstract = {Clones are generally considered bad programming practice in software engineering folklore. They are identified as a bad smell (Fowler et al. 1999) and a major contributor to project maintenance difficulties. Clones inherently cause code bloat, thus increasing project size and maintenance costs. In this work, we try to validate the conventional wisdom empirically to see whether cloning makes code more defect prone. This paper analyses the relationship between cloning and defect proneness. For the four medium to large open source projects that we studied, we find that, first, the great majority of bugs are not significantly associated with clones. Second, we find that clones may be less defect prone than non-cloned code. Third, we find little evidence that clones with more copies are actually more error prone. Fourth, we find little evidence to support the claim that clone groups that span more than one file or directory are more defect prone than collocated clones. Finally, we find that developers do not need to put a disproportionately higher effort to fix clone dense bugs. Our findings do not support the claim that clones are really a {\textquotedblleft}bad smell{\textquotedblright} (Fowler et al. 1999). Perhaps we can clone, and breathe easily, at the same time. },
	issn = {1573-7616},
	doi = {10.1007/s10664-011-9195-3},
	author = {Rahman, Foyzur and Christian Bird and Devanbu, Premkumar}
}
@conference {954,
	title = {Clones: What is that smell?},
	booktitle = {2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)},
	year = {2010},
	pages = {72 - 81},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {Clones are generally considered bad programming practice in software engineering folklore. They are identified as a bad smell and a major contributor to project maintenance difficulties. Clones inherently cause code bloat, thus increasing project size and maintenance costs. In this work, we try to validate the conventional wisdom empirically to see whether cloning makes code more defect prone. This paper analyses relationship between cloning and defect proneness. We find that, first, the great majority of bugs are not significantly associated with clones. Second, we find that clones may be less defect prone than non-cloned code. Finally, we find little evidence that clones with more copies are actually more error prone. Our findings do not support the claim that clones are really a "bad smell". Perhaps we can clone, and breathe easy, at the same time.},
	keywords = {apache, bug fix revisions, bugs, clone, evolution, gimp, nautilus, scm, source code},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463343},
	attachments = {https://flosshub.org/sites/flosshub.org/files/72rahman2010cws.pdf},
	author = {Rahman, Foyzur and Christian Bird and Devanbu, Premkumar}
}
@conference {bird2010lee,
	title = {{Linkster: Enabling Efficient Manual Mining}},
	booktitle = {Demonstration Track, Proceedings of the 17th SIGSOFT Symposium on Foundations of Software Engineering},
	year = {2010},
	note = {"LINKSTER efficiently displays, integrates, and allows inspection and annotation of information from three main sources of data: source code repositories, developer mailing lists archives, and bug tracking databases. LINKSTER requires access to a source code repository for file content and a database which contains the raw mined repository, mailing list, and bug tracking information. All notes and annotations made by the user are also recorded in the database."},
	publisher = {ACM},
	organization = {ACM},
	abstract = {While many uses of mined software engineering data are automatic in nature, some techniques and studies either require, or can be improved, by manual methods. Unfortunately, manually inspecting, analyzing, and annotating mined data can be difficult and tedious, especially when information from multiple sources must be integrated. Oddly, while there are numerous tools and frameworks for automatically mining and analyzing data, there is a dearth of tools which facilitate manual methods. To fill this void, we have developed LINKSTER, a tool which integrates data from bug databases, source code repositories, and mailing list archives to allow manual inspection and annotation. LINKSTER has already been used successfully by an OSS project lead to obtain data for one empirical study.},
	keywords = {artifacts, bug, bug tracking, data mining, email, mailing lists, open source, source code},
	attachments = {https://flosshub.org/sites/flosshub.org/files/bird2010lee.pdf},
	author = {Christian Bird and Adrian Bachman and Rahman, Foyzur and Bernstein, Abraham}
}
