Prereqir: Recovering Pre-Requirements via Cluster Analysis. Hayes, J. H., Antoniol, G., & Gu�h�neuc, Y. In Zaidman, A., Di Penta, M., & Hassan, A., editors, Proceedings of the 15<sup>th</sup> Working Conference on Reverse Engineering (WCRE), pages 165–174, October, 2008. IEEE CS Press. 10 pages.
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Paper abstract bibtex
Paper abstract bibtex High-level software artifacts, such as requirements, domain-specific requirements, and so on, are an important source of information that is often neglected during the reverse- and re-engineering processes. We posit that domain specific pre-requirements information (PRI) can be obtained by eliciting the stakeholders' understanding of generic systems or domains. We discuss the semi-automatic recovery of domain-specific PRI that can then be used during reverse- and re-engineering, for example, to recover traceability links or to assess the degree of obsolescence of a system with respect to competing systems and the clients' expectations. We present a method using partition around medoids and agglomerative clustering for obtaining, structuring, analyzing, and labeling textual PRI from a group of diverse stakeholders. We validate our method using PRI for the development of a generic Web browser provided by 22 different stakeholders. We show that, for a similarity threshold of about 0.36, about 55% of the PRI were common to two or more stakeholders and 42% were outliers. We automatically label the common and outlier PRI (82% correctly labeled), and obtain 74% accuracy for the similarity threshold of 0.36 (78% for a threshold of 0.5). We assess the recall and precision of the method, and compare the labeled PRI to a generic Web browser requirements specification.
@INPROCEEDINGS{Hayes08-WCRE-PREREQIR,
AUTHOR = {Jane Huffman Hayes and Giuliano Antoniol and
Yann-Ga�l Gu�h�neuc},
BOOKTITLE = {Proceedings of the 15<sup>th</sup> Working Conference on Reverse Engineering (WCRE)},
TITLE = {Prereqir: Recovering Pre-Requirements via Cluster
Analysis},
YEAR = {2008},
OPTADDRESS = {},
OPTCROSSREF = {},
EDITOR = {Andy Zaidman and Di Penta, Massimilano and Ahmed Hassan},
MONTH = {October},
NOTE = {10 pages.},
OPTNUMBER = {},
OPTORGANIZATION = {},
PAGES = {165--174},
PUBLISHER = {IEEE CS Press},
OPTSERIES = {},
OPTVOLUME = {},
KEYWORDS = {Topic: <b>Requirements and features</b>,
Venue: <c>WCRE</c>},
URL = {http://www.ptidej.net/publications/documents/WCRE08.doc.pdf},
PDF = {http://www.ptidej.net/publications/documents/WCRE08.ppt.pdf},
ABSTRACT = {High-level software artifacts, such as requirements,
domain-specific requirements, and so on, are an important source of
information that is often neglected during the reverse- and
re-engineering processes. We posit that domain specific
pre-requirements information (PRI) can be obtained by eliciting the
stakeholders' understanding of generic systems or domains. We discuss
the semi-automatic recovery of domain-specific PRI that can then be
used during reverse- and re-engineering, for example, to recover
traceability links or to assess the degree of obsolescence of a
system with respect to competing systems and the clients'
expectations. We present a method using partition around medoids and
agglomerative clustering for obtaining, structuring, analyzing, and
labeling textual PRI from a group of diverse stakeholders. We
validate our method using PRI for the development of a generic Web
browser provided by 22 different stakeholders. We show that, for a
similarity threshold of about 0.36, about 55\% of the PRI were common
to two or more stakeholders and 42\% were outliers. We automatically
label the common and outlier PRI (82\% correctly labeled), and obtain
74\% accuracy for the similarity threshold of 0.36 (78\% for a
threshold of 0.5). We assess the recall and precision of the method,
and compare the labeled PRI to a generic Web browser requirements
specification.}
}Downloads: 0
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We posit that domain specific pre-requirements information (PRI) can be obtained by eliciting the stakeholders' understanding of generic systems or domains. We discuss the semi-automatic recovery of domain-specific PRI that can then be used during reverse- and re-engineering, for example, to recover traceability links or to assess the degree of obsolescence of a system with respect to competing systems and the clients' expectations. We present a method using partition around medoids and agglomerative clustering for obtaining, structuring, analyzing, and labeling textual PRI from a group of diverse stakeholders. We validate our method using PRI for the development of a generic Web browser provided by 22 different stakeholders. We show that, for a similarity threshold of about 0.36, about 55% of the PRI were common to two or more stakeholders and 42% were outliers. 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