SCAN: An Approach to Label and Relate Execution Trace Segments. Medini, S., Arnaoudova, V., Di Penta, M., Antoniol, G., Gu�h�neuc, Y., & Tonella, P. Journal of Software: Evolution and Process (JSEP), 26(11):962–995, Wiley, November, 2014. 33 pages.
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Paper abstract bibtex
Paper abstract bibtex Program comprehension is a prerequisite to any maintenance and evolution task. In particular, when performing feature location, developers perform program comprehension by abstracting software features and identifying the links between high-level abstractions (features) and program elements. We present Segment Concept AssigNer (SCAN), an approach to support developers in feature location. SCAN uses a search-based approach to split execution traces into cohesive segments. Then, it labels the segments with relevant keywords and, finally, uses formal concept analysis to identify relations among segments. In a first study, we evaluate the performances of SCAN on six Java programs by 31 participants. We report an average precision of 69\NOand a recall of 63\NOwhen comparing the manual and automatic labels and a precision of 63\NOregarding the relations among segments identified by SCAN. After that, we evaluate the usefulness of SCAN for the purpose of feature location on two Java programs. We provide evidence that SCAN (i) identifies 69\NOof the gold set methods and (ii) is effective in reducing the quantity of information that developers must process to locate features—reducing the number of methods to understand by an average of 43\NOcompared to the entire execution traces.
@ARTICLE{Medini14-JSEP-SCAN,
AUTHOR = {Soumaya Medini and Venera Arnaoudova and
Di Penta, Massimiliano and Giulian Antoniol and Yann-Ga�l Gu�h�neuc and
Paolo Tonella},
JOURNAL = {Journal of Software: Evolution and Process (JSEP)},
TITLE = {SCAN: An Approach to Label and Relate Execution Trace
Segments},
YEAR = {2014},
MONTH = {November},
NOTE = {33 pages.},
NUMBER = {11},
PAGES = {962--995},
VOLUME = {26},
EDITOR = {Rocco Oliveto and Denys Poshyvanyk},
KEYWORDS = {Topic: <b>Requirements and features</b>,
Venue: <b>JSEP</b>},
PUBLISHER = {Wiley},
URL = {http://www.ptidej.net/publications/documents/JSEP14.doc.pdf},
ABSTRACT = {Program comprehension is a prerequisite to any
maintenance and evolution task. In particular, when performing
feature location, developers perform program comprehension by
abstracting software features and identifying the links between
high-level abstractions (features) and program elements. We present
Segment Concept AssigNer (SCAN), an approach to support developers in
feature location. SCAN uses a search-based approach to split
execution traces into cohesive segments. Then, it labels the segments
with relevant keywords and, finally, uses formal concept analysis to
identify relations among segments. In a first study, we evaluate the
performances of SCAN on six Java programs by 31 participants. We
report an average precision of 69\NOand a recall of 63\NOwhen
comparing the manual and automatic labels and a precision of
63\NOregarding the relations among segments identified by SCAN. After
that, we evaluate the usefulness of SCAN for the purpose of feature
location on two Java programs. We provide evidence that SCAN (i)
identifies 69\NOof the gold set methods and (ii) is effective in
reducing the quantity of information that developers must process to
locate features---reducing the number of methods to understand by an
average of 43\NOcompared to the entire execution traces.}
}Downloads: 0
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