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Feature Vectors for Performance Test Case Classification

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Advanced Multimedia and Ubiquitous Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 393))

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Abstract

This paper proposes a feature-vector for characterizing performance test cases. The feature-vector is composed of six attributes such as use of thread, measuring elapsed time and counting successful and failed number of test cases. In order to identify the feature vector, we thoroughly examined the test cases from five open source projects and extracted performance cases. After then, we established the common feature vector discovered from the performance test cases, and analyzed distribution of the feature vector in the performance as well as general test cases to show the validity of the feature-vector.

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Acknowledgments

This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2014M3C4A7030503)

Author information

Authors and Affiliations

  1. Department of Software Engineering, CAIIT, Chonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeollabuk-do, Jeonju-si, 54896, Republic of Korea

    Calvin G. Mangeni & Suntae Kim

  2. Department of Computer Engineering, Kangwon National University, Joongang-ro, Kangwon-do, Samcheck-si, Republic of Korea

    Rhan Jung

Authors
  1. Calvin G. Mangeni
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  2. Suntae Kim
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  3. Rhan Jung
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Corresponding author

Correspondence to Suntae Kim .

Editor information

Editors and Affiliations

  1. Computer Science and Engg., Seoul National Uni. of Sci. & Techn. Computer Science and Engg., Seoul, Korea (Republic of)

    James J. (Jong Hyuk) Park

  2. School of Comp. Science and Technology, Huazhong Univ. of Science and Technology School of Comp. Science and Technology, Wuhan, China

    Hai Jin

  3. Dept. of Multimedia Eng., Dongguk University Dept. of Multimedia Eng., Seoul, Korea (Republic of)

    Young-Sik Jeong

  4. College of Computer & Information Sci, King Saud University College of Computer & Information Sci, Riyadh, Saudi Arabia

    Muhammad Khurram Khan

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© 2016 Springer Science+Business Media Singapore

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Cite this paper

Mangeni, C.G., Kim, S., Jung, R. (2016). Feature Vectors for Performance Test Case Classification. In: Park, J., Jin, H., Jeong, YS., Khan, M. (eds) Advanced Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 393. Springer, Singapore. https://doi.org/10.1007/978-981-10-1536-6_55

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  • DOI: https://doi.org/10.1007/978-981-10-1536-6_55

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1535-9

  • Online ISBN: 978-981-10-1536-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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