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Relevance-based abstraction identification: technique and evaluation

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Relevance-based abstraction identification: technique and evaluation. / Gacitua, Ricardo; Sawyer, Peter; Gervasi, Vincenzo.
In: Requirements Engineering , Vol. 16, No. 3, 09.2011, p. 251-265.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Gacitua, R, Sawyer, P & Gervasi, V 2011, 'Relevance-based abstraction identification: technique and evaluation', Requirements Engineering , vol. 16, no. 3, pp. 251-265. https://doi.org/10.1007/s00766-011-0122-3

APA

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

Vancouver

Gacitua R, Sawyer P, Gervasi V. Relevance-based abstraction identification: technique and evaluation. Requirements Engineering . 2011 Sept;16(3):251-265. doi: 10.1007/s00766-011-0122-3

Author

Gacitua, Ricardo ; Sawyer, Peter ; Gervasi, Vincenzo. / Relevance-based abstraction identification: technique and evaluation. In: Requirements Engineering . 2011 ; Vol. 16, No. 3. pp. 251-265.

Bibtex

@article{6aec22a829814a2caf53d5d5a57ce815,
title = "Relevance-based abstraction identification: technique and evaluation",
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.",
keywords = "Abstractions , Natural language , Requirements elicitation , Evaluation of tool",
author = "Ricardo Gacitua and Peter Sawyer and Vincenzo Gervasi",
year = "2011",
month = sep,
doi = "10.1007/s00766-011-0122-3",
language = "English",
volume = "16",
pages = "251--265",
journal = "Requirements Engineering ",
issn = "0947-3602",
publisher = "Springer London",
number = "3",

}

RIS

TY - JOUR

T1 - Relevance-based abstraction identification: technique and evaluation

AU - Gacitua, Ricardo

AU - Sawyer, Peter

AU - Gervasi, Vincenzo

PY - 2011/9

Y1 - 2011/9

N2 - 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.

AB - 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.

KW - Abstractions

KW - Natural language

KW - Requirements elicitation

KW - Evaluation of tool

UR - http://www.scopus.com/inward/record.url?scp=84870583552&partnerID=8YFLogxK

U2 - 10.1007/s00766-011-0122-3

DO - 10.1007/s00766-011-0122-3

M3 - Journal article

VL - 16

SP - 251

EP - 265

JO - Requirements Engineering

JF - Requirements Engineering

SN - 0947-3602

IS - 3

ER -