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Traceability challenge 2011.

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Title: Traceability challenge 2011.
Authors: Czauderna, Adam, Gibiec, Marek, Leach, Greg, Li, Yubin, Shin, Yonghee, Keenan, Ed, Cleland-Huang, Jane
Source: ICSE: International Conference on Software Engineering. 2011, p75-78. 4p.
Subjects: Algorithms, Workflow software, Computer software, Systems design, Software engineering
Abstract: Numerous trace retrieval algorithms incorporate the standard tf-idf (term frequency, inverse document frequency) technique to weight various terms. In this paper we address Grand Challenge C-GC1 by comparing the effectiveness of computing idf based only on the local terms in the query, versus computing it based on general term usage as documented in the American National Corpus. We also address Grand Challenges L-GC1 and L-GC2 by setting ourselves the additional task of designing and conducting the experiments using the alpha-release of TraceLab. TraceLab is an experimental workbench which allows researchers to graphically model and execute a traceability experiment as a workflow of components. Results of the experiment show that the local idf approach exceeds or matches the global approach in all of the cases studied. [ABSTRACT FROM AUTHOR]
Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Header DbId: egs
DbLabel: Engineering Source
An: 71531586
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PubType: Conference
PubTypeId: conference
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  Data: Traceability challenge 2011.
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  Data: <searchLink fieldCode="AR" term="%22Czauderna%2C+Adam%22">Czauderna, Adam</searchLink><br /><searchLink fieldCode="AR" term="%22Gibiec%2C+Marek%22">Gibiec, Marek</searchLink><br /><searchLink fieldCode="AR" term="%22Leach%2C+Greg%22">Leach, Greg</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Yubin%22">Li, Yubin</searchLink><br /><searchLink fieldCode="AR" term="%22Shin%2C+Yonghee%22">Shin, Yonghee</searchLink><br /><searchLink fieldCode="AR" term="%22Keenan%2C+Ed%22">Keenan, Ed</searchLink><br /><searchLink fieldCode="AR" term="%22Cleland-Huang%2C+Jane%22">Cleland-Huang, Jane</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22ICSE%3A+International+Conference+on+Software+Engineering%22">ICSE: International Conference on Software Engineering</searchLink>. 2011, p75-78. 4p.
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  Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Workflow+software%22">Workflow software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+design%22">Systems design</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink>
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  Data: Numerous trace retrieval algorithms incorporate the standard tf-idf (term frequency, inverse document frequency) technique to weight various terms. In this paper we address Grand Challenge C-GC1 by comparing the effectiveness of computing idf based only on the local terms in the query, versus computing it based on general term usage as documented in the American National Corpus. We also address Grand Challenges L-GC1 and L-GC2 by setting ourselves the additional task of designing and conducting the experiments using the alpha-release of TraceLab. TraceLab is an experimental workbench which allows researchers to graphically model and execute a traceability experiment as a workflow of components. Results of the experiment show that the local idf approach exceeds or matches the global approach in all of the cases studied. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of ICSE: International Conference on Software Engineering is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1145/1987856.1987874
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      – Code: eng
        Text: English
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        PageCount: 4
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      – SubjectFull: Algorithms
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              Text: 2011
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            – TitleFull: ICSE: International Conference on Software Engineering
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