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A Novel Bug Report Extraction Approach

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Algorithms and Architectures for Parallel Processing (ICA3PP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9532))

Abstract

There are more and more bug reports in software. Software companies and developers invest a large number of resources into the dramatic accumulation of reports. We introduce Bayes classifier into bug reports compression, which is the first effort in the literature. For this purpose, the vector space model as well as some conventional text mining values, such as tf-idf and chi-squared test, are designed to collect features for bug reports. The experiment proves that bug reports extraction by using Bayes classifier is outperformance to the method based on SVM through the evaluation of ROC and F-score.

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Notes

  1. 1.

    www.cs.ubc.ca/cs-research/software-practices-lab/projects/summarizing-software-artifacts, verified 2015/09/04.

  2. 2.

    http://textblob.readthedocs.org/en/dev/, verified 2015/09/04.

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Acknowledgments

This work was supported by the National Science Foundation of China, No. 61073163, and Enterprise Innovation Special Fund of Shanghai Municipal Commisiion of Economy and Informatization, China, No. CXY-2013-88.

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Shanghai Normal University, Shanghai, 200234, China

    Tao Lin, Jianhua Gao & Xue Fu

  2. Department of Information Systems and Operations Management, The University of Auckland, Auckland, 92019, New Zealand

    Yan Lin

Authors
  1. Tao Lin
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  2. Jianhua Gao
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  3. Xue Fu
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  4. Yan Lin
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Corresponding author

Correspondence to Tao Lin .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Guojin Wang

  2. Sch of Information Technologies, Sydney University, Sydney, New South Wales, Australia

    Albert Zomaya

  3. Department of Information and Commu, University of Murcia, Murcia, Murcia, Spain

    Gregorio Martinez

  4. Changsha, China

    Kenli Li

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© 2015 Springer International Publishing Switzerland

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Lin, T., Gao, J., Fu, X., Lin, Y. (2015). A Novel Bug Report Extraction Approach. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9532. Springer, Cham. https://doi.org/10.1007/978-3-319-27161-3_70

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  • DOI: https://doi.org/10.1007/978-3-319-27161-3_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27160-6

  • Online ISBN: 978-3-319-27161-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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