IEICE TRANSACTIONS on Information
Automating Bad Smell Detection in Goal Refinement of Goal Models
Summary :
Goal refinement is a crucial step in goal-oriented requirements analysis to create a goal model of high quality. Poor goal refinement leads to missing requirements and eliciting incorrect requirements as well as less comprehensiveness of produced goal models. This paper proposes a technique to automate detecting bad smells of goal refinement, symptoms of poor goal refinement. At first, to clarify bad smells, we asked subjects to discover poor goal refinement concretely. Based on the classification of the specified poor refinement, we defined four types of bad smells of goal refinement: Low Semantic Relation, Many Siblings, Few Siblings, and Coarse Grained Leaf, and developed two types of measures to detect them: measures on the graph structure of a goal model and semantic similarity of goal descriptions. We have implemented a supporting tool to detect bad smells and assessed its usefulness by an experiment.
- Publication
- IEICE TRANSACTIONS on Information Vol.E105-D No.5 pp.837-848
- Publication Date
- 2022/05/01
- Publicized
- 2022/01/06
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2021KBP0006
- Type of Manuscript
- Special Section PAPER (Special Section on Knowledge-Based Software Engineering)
- Category
Authors
Shinpei HAYASHI
Tokyo Institute of Technology
Keisuke ASANO
Tokyo Institute of Technology
Motoshi SAEKI
Nanzan University
Keyword
Latest Issue
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Shinpei HAYASHI, Keisuke ASANO, Motoshi SAEKI, "Automating Bad Smell Detection in Goal Refinement of Goal Models" in IEICE TRANSACTIONS on Information,
vol. E105-D, no. 5, pp. 837-848, May 2022, doi: 10.1587/transinf.2021KBP0006.
Abstract: Goal refinement is a crucial step in goal-oriented requirements analysis to create a goal model of high quality. Poor goal refinement leads to missing requirements and eliciting incorrect requirements as well as less comprehensiveness of produced goal models. This paper proposes a technique to automate detecting bad smells of goal refinement, symptoms of poor goal refinement. At first, to clarify bad smells, we asked subjects to discover poor goal refinement concretely. Based on the classification of the specified poor refinement, we defined four types of bad smells of goal refinement: Low Semantic Relation, Many Siblings, Few Siblings, and Coarse Grained Leaf, and developed two types of measures to detect them: measures on the graph structure of a goal model and semantic similarity of goal descriptions. We have implemented a supporting tool to detect bad smells and assessed its usefulness by an experiment.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021KBP0006/_p
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@ARTICLE{e105-d_5_837,
author={Shinpei HAYASHI, Keisuke ASANO, Motoshi SAEKI, },
journal={IEICE TRANSACTIONS on Information},
title={Automating Bad Smell Detection in Goal Refinement of Goal Models},
year={2022},
volume={E105-D},
number={5},
pages={837-848},
abstract={Goal refinement is a crucial step in goal-oriented requirements analysis to create a goal model of high quality. Poor goal refinement leads to missing requirements and eliciting incorrect requirements as well as less comprehensiveness of produced goal models. This paper proposes a technique to automate detecting bad smells of goal refinement, symptoms of poor goal refinement. At first, to clarify bad smells, we asked subjects to discover poor goal refinement concretely. Based on the classification of the specified poor refinement, we defined four types of bad smells of goal refinement: Low Semantic Relation, Many Siblings, Few Siblings, and Coarse Grained Leaf, and developed two types of measures to detect them: measures on the graph structure of a goal model and semantic similarity of goal descriptions. We have implemented a supporting tool to detect bad smells and assessed its usefulness by an experiment.},
keywords={},
doi={10.1587/transinf.2021KBP0006},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Automating Bad Smell Detection in Goal Refinement of Goal Models
T2 - IEICE TRANSACTIONS on Information
SP - 837
EP - 848
AU - Shinpei HAYASHI
AU - Keisuke ASANO
AU - Motoshi SAEKI
PY - 2022
DO - 10.1587/transinf.2021KBP0006
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E105-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2022
AB - Goal refinement is a crucial step in goal-oriented requirements analysis to create a goal model of high quality. Poor goal refinement leads to missing requirements and eliciting incorrect requirements as well as less comprehensiveness of produced goal models. This paper proposes a technique to automate detecting bad smells of goal refinement, symptoms of poor goal refinement. At first, to clarify bad smells, we asked subjects to discover poor goal refinement concretely. Based on the classification of the specified poor refinement, we defined four types of bad smells of goal refinement: Low Semantic Relation, Many Siblings, Few Siblings, and Coarse Grained Leaf, and developed two types of measures to detect them: measures on the graph structure of a goal model and semantic similarity of goal descriptions. We have implemented a supporting tool to detect bad smells and assessed its usefulness by an experiment.
ER -
English
