A Heuristic-based Approach to Identify Concepts in Execution Traces. Asadi, F., Di Penta, M., Antoniol, G., & Gu�h�neuc, Y. In Ferenc, R. & Due�as, J. C., editors, Proceedings of the 14<sup>th</sup> European Conference on Software Maintenance and Reengineering (CSMR), pages 31–40, March, 2010. IEEE CS Press. 10 pages.
Paper abstract bibtex Concept or feature identification, ıe the identification of the source code fragments implementing a particular feature, is a crucial task during software understanding and maintenance. This paper proposes an approach to identify concepts in execution traces by finding cohesive and decoupled fragments of the traces. The approach relies on search-based optimization techniques, textual analysis of the system source code using latent semantic indexing, and trace compression techniques. It is evaluated to identify features from execution traces of two open source systems from different domains, JHotDraw and ArgoUML. Results show that the approach is always able to identify trace segments implementing concepts with a high precision and, for highly cohesive concepts, with a high overlap with the manually-built oracle.
@INPROCEEDINGS{Asadi10-CSMR-IdentifyConceptsTraces,
AUTHOR = {Fatemeh Asadi and Di Penta, Massimiliano and
Giuliano Antoniol and Yann-Ga�l Gu�h�neuc},
BOOKTITLE = {Proceedings of the 14<sup>th</sup> European Conference on Software Maintenance and Reengineering (CSMR)},
TITLE = {A Heuristic-based Approach to Identify Concepts in
Execution Traces},
YEAR = {2010},
OPTADDRESS = {},
OPTCROSSREF = {},
EDITOR = {Rudolf Ferenc and Juan Carlos Due�as},
MONTH = {March},
NOTE = {10 pages.},
OPTNUMBER = {},
OPTORGANIZATION = {},
PAGES = {31--40},
PUBLISHER = {IEEE CS Press},
OPTSERIES = {},
OPTVOLUME = {},
KEYWORDS = {Topic: <b>Requirements and features</b>,
Venue: <c>CSMR</c>},
URL = {http://www.ptidej.net/publications/documents/CSMR10a.doc.pdf},
PDF = {http://www.ptidej.net/publications/documents/CSMR10a.ppt.pdf},
ABSTRACT = {Concept or feature identification, \ie{} the
identification of the source code fragments implementing a particular
feature, is a crucial task during software understanding and
maintenance. This paper proposes an approach to identify concepts in
execution traces by finding cohesive and decoupled fragments of the
traces. The approach relies on search-based optimization techniques,
textual analysis of the system source code using latent semantic
indexing, and trace compression techniques. It is evaluated to
identify features from execution traces of two open source systems
from different domains, JHotDraw and ArgoUML. Results show that the
approach is always able to identify trace segments implementing
concepts with a high precision and, for highly cohesive concepts,
with a high overlap with the manually-built oracle.}
}
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