AURA: A Hybrid Approach to Identify Framework Evolution. Wu, W., Gu�h�neuc, Y., Antoniol, G., & Kim, M. In Devanbu, P. & Uchitel, S., editors, Proceedings of the 32<sup>nd</sup> International Conference on Software Engineering (ICSE), pages 325–334, May, 2010. ACM Press. 10 pages.
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Paper abstract bibtex
Paper abstract bibtex Software frameworks and libraries are indispensable to today's software systems. As they evolve, it is often time-consuming for developers to keep their code up-to-date, so approaches have been proposed to facilitate this. Usually, these approaches cannot automatically identify change rules for one-replaced-by-many and many-replaced-by-one methods, and they trade off recall for higher precision using one or more experimentally-evaluated thresholds. We introduce AURA, a novel hybrid approach that combines call dependency and text similarity analyses to overcome these limitations. We implement it in a Java system and compare it on five frameworks with three previous approaches by Dagenais and Robillard, M.\ Kim \ygg@latinet al., and Schäfer \ygg@latinet al. The comparison shows that, on average, the recall of AURA is 53.07\NOhigher while its precision is similar, \ygg@latine.g., 0.10\NOlower.
@INPROCEEDINGS{Wu10-ICSE-AURA,
AUTHOR = {Wei Wu and Yann-Ga�l Gu�h�neuc and Giuliano Antoniol and
Miryung Kim},
BOOKTITLE = {Proceedings of the 32<sup>nd</sup> International Conference on Software Engineering (ICSE)},
TITLE = {AURA: A Hybrid Approach to Identify Framework Evolution},
YEAR = {2010},
OPTADDRESS = {},
OPTCROSSREF = {},
EDITOR = {Prem Devanbu and Sebastian Uchitel},
MONTH = {May},
NOTE = {10 pages.},
OPTNUMBER = {},
OPTORGANIZATION = {},
PAGES = {325--334},
PUBLISHER = {ACM Press},
OPTSERIES = {},
OPTVOLUME = {},
KEYWORDS = {Topic: <b>Evolution patterns</b>, Venue: <c>ICSE</c>},
URL = {http://www.ptidej.net/publications/documents/ICSE10b.doc.pdf},
PDF = {http://www.ptidej.net/publications/documents/ICSE10b.ppt.pdf},
ABSTRACT = {Software frameworks and libraries are indispensable to
today's software systems. As they evolve, it is often time-consuming
for developers to keep their code up-to-date, so approaches have been
proposed to facilitate this. Usually, these approaches cannot
automatically identify change rules for one-replaced-by-many and
many-replaced-by-one methods, and they trade off recall for higher
precision using one or more experimentally-evaluated thresholds. We
introduce AURA, a novel hybrid approach that combines call dependency
and text similarity analyses to overcome these limitations. We
implement it in a Java system and compare it on five frameworks with
three previous approaches by Dagenais and Robillard, M.\ Kim
\ygg@latin{et al.}, and Sch\"afer \ygg@latin{et al.} The comparison
shows that, on average, the recall of AURA is 53.07\NOhigher while
its precision is similar, \ygg@latin{e.g.}, 0.10\NOlower.}
}Downloads: 0
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