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Analyzing Empirical Data in Requirements Engineering Techniques

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Information Systems Development

  • 2005 Accesses

Abstract

Getting meaningful information from empirical data is a challenging task in software engineering (SE). It requires an in-depth analysis of the research problem, the data obtained and to select the most suitable data analysis methods, as well as an evaluation of the validity of the analysis result. This chapter reports research with three data analysis methods that were used to analyze a set of empirical requirements techniques data. One of the major findings is that it is possible to get better analysis results if several data analysis methods are combined. The way to examine the validity of the results is also explored.

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Notes

  1. 1.

    As RE techniques are a subset of SE techniques, we infer that the research results derived from RE techniques analysis will be applicable to SE techniques analysis.

  2. 2.

    We acknowledge the differences between the two terms “method” and “technique” as used in the SE research community and the disparities of the definitions given for these two terms in academia. The term “method” is deliberately used in this chapter to refer to any one or more algorithms and/or methods created for data clustering and data analysis. The purpose of adopting this terminology (in this chapter only) is to differentiate the two terms “method” and “technique” with the latter referring to SE techniques or methods.

  3. 3.

    A sufficient statistic refers to a statistic that has the property of sufficiency with respect to a statistical model and its associated unknown parameter θ that are used in statistical calculation and reasoning (Hogg and Craig 1978), i.e., no other statistic that can be calculated from the same data set provides any additional information as to the value of the parameter θ.

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Author information

Authors and Affiliations

  1. School of Computer Science, The University of Adelaide, Adelaide, SA, Australia

    Li Jiang

  2. Computer Engineering Department, American University of Sharjah, Sharjah, UAE

    Armin Eberlein

  3. Curtin University of Technology, Perth, WA, 6102, Australia

    Aneesh Krishna

Authors
  1. Li Jiang
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  2. Armin Eberlein
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  3. Aneesh Krishna
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Corresponding author

Correspondence to Li Jiang .

Editor information

Editors and Affiliations

  1. Heriot-Watt University Edinburgh Dept. Computer Science, Edinburgh, United Kingdom

    Rob Pooley

  2. Heriot-Watt University Edinburgh Dept. Computer Science, Edinburgh, United Kingdom

    Jennifer Coady

  3. City University of Hong Kong, Kowloon, Hong Kong SAR

    Christoph Schneider

  4. Monash University Fac. Information Technology, Clayton, Victoria, Australia

    Henry Linger

  5. National University of Ireland, Galway, Ireland

    Chris Barry

  6. National University of Ireland, Galway, Ireland

    Michael Lang

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Jiang, L., Eberlein, A., Krishna, A. (2013). Analyzing Empirical Data in Requirements Engineering Techniques. In: Pooley, R., Coady, J., Schneider, C., Linger, H., Barry, C., Lang, M. (eds) Information Systems Development. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4951-5_29

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  • DOI: https://doi.org/10.1007/978-1-4614-4951-5_29

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-4950-8

  • Online ISBN: 978-1-4614-4951-5

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