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Relevance-based abstraction identification: technique and evaluation

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Abstract

When first approaching an unfamiliar domain or requirements document, it is often useful to get a quick grasp of what the essential concepts and entities in the domain are. This process is called abstraction identification, where the word abstraction refers to an entity or concept that has a particular significance in the domain. Abstraction identification has been proposed and evaluated as a useful technique in requirements engineering (RE). In this paper, we propose a new technique for automated abstraction identification called relevance-based abstraction identification (RAI), and evaluate its performance—in multiple configurations and through two refinements—compared to other tools and techniques proposed in the literature, where we find that RAI significantly outperforms previous techniques. We present an experiment measuring the effectiveness of RAI compared to human judgement, and discuss how RAI could be used to good effect in requirements engineering.

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Acknowledgments

This work was funded by EPSRC grant EP/F069227/1 MaTREx.

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Authors and Affiliations

  1. School of Computing and Communications, Lancaster University, Lancaster, UK

    Ricardo Gacitua & Pete Sawyer

  2. Dipartimento di Informatica, Università di Pisa, Pisa, Italy

    Vincenzo Gervasi

Authors
  1. Ricardo Gacitua
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  2. Pete Sawyer
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  3. Vincenzo Gervasi
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Correspondence to Ricardo Gacitua.

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Gacitua, R., Sawyer, P. & Gervasi, V. Relevance-based abstraction identification: technique and evaluation. Requirements Eng 16, 251–265 (2011). https://doi.org/10.1007/s00766-011-0122-3

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