• Annual Conference of KIPS
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• 2013.11a
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• pp.1011-1014
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• 2013

기존 논문에서는 Fillmore의 Case Grammar를 적용한 객체 추출 및 유스케이스 모델링 방법을 제안하였다[1]. 이 방법은 정확한 요구사항 분석이 가능하지만, 유스케이스 추출 및 규모 결정 방법을 고려하지 않았다. 이러한 문제를 해결하기 위해, 본 논문에서는 Fillmore의 Case Grammar를 적용한 유스케이스 추출 및 규모 결정 방법을 제안한다. 언어학자인 Fillmore의 방법을 요구공학에 적용하기 위해서, 그의 메커니즘 개선을 통해 구조화 절차 메커니즘 정의와 표기법(Notation) 변경을 수행하였다. 이 절차에 의해, 정확한 Goal 유스케이스 모델링과 유스케이스 식별이 용이하다. 또한 정확한 유스케이스 추출 및 규모 결정이 가능하다. 사례연구로 은행 ATM 시스템에 적용하였다.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.255-262
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• 2014

Our previous research[1] suggested object extraction and modeling method based on Fillmore's case grammar. This approach had not considered of use case extraction and method. To solve this problem, we adopt Fillmore's semantic method as linguistic approach into requirement engineering, which refine fillmore's case grammar for extracting and modeling use cases from customer requirements. This Refined mechanism includes the definition of a structured procedure and the representation of visual notations for 'case' modeling. This paper also proposes the use case decision matrix to identify use case size from extracted use cases based on goal oriented requirement engineering(GoRE), which related with the complexity of use case, and also prioritizes the use cases with this matrix. It demonstrates our proposal with the bank ATM system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.985-989
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• 2010

The near future smart ubiquitous computing oriented system will have to provide the optimal (right) service through interactions between users and the system. To provide the right services what the user needs, we should choose the user-centered development for reflecting the user needs, but not the developer-centered development. To do this, we proposed User Behavior Analysis Based Needs Extraction Method [1]. In this paper, we propose Object Extraction and Modeling Method from the user requirements with Fillmore's Case Grammar.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.3-4
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• 2010

미래의 스마트 유비쿼터스 컴퓨팅 기반 시스템은 사용자들과 상호작용을 통해 적절한 서비스를 제공이 가능 할 것이다. 사용자 요구(Needs)에 맞는 서비스를 제공하려면 기존의 개발자 중심의 개발보다 사용자의 요구를 반영하는 사용자 중심의 시스템 개발이 필요할 것이다. 이를 위해 이전 논문[1]에서는 사용자 행위 분석 기반 요구 추출방법(User Behavior Analysis Based Needs Extraction Method)을 제안하였다. 본 논문에서는 추출된 사용자의 요구사항을 Fillmore의 Case Grammar을 이용하여 객체 추출 및 모델링 방법을 제안한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.97-103
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• 2017

For high quality of software, it should be necessary for defining and analyzing the exact requirements at the early stage of software development. But readability and understandability of most natural language requirements are inaccurate and difficult for identifying use cases. The requirements are duplicated for objects or temrs with the same meaning. To solve this problem, it should need an effective way of requirement analysis based on linguistic and semantic textual analysis. In this paper, we propose to improve a semantic analysis method adopted with a linguist Fillmore's linguistic mechanism. This method may expect to analyze easily readable and exactly understandable requirements specifications through modeling the goal oriented use cases with natural language based requirements.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.99-107
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• 2024

In AI image generation tools, most general users must use an effective prompt to craft queries or statements to elicit the desired response (image, result) from the AI model. But we are software engineers who focus on software processes. At the process's early stage, we use informal and formal requirement specifications. At this time, we adapt the natural language approach into requirement engineering and toon engineering. Most Generative AI tools do not produce the same image in the same query. The reason is that the same data asset is not used for the same query. To solve this problem, we intend to use informal requirement engineering and linguistics to create a toon. Therefore, we propose a sequence diagram and image generation mechanism by analyzing and applying key objects and attributes as an informal natural language requirement analysis. Identify morpheme and semantic roles by analyzing natural language through linguistic methods. Based on the analysis results, a sequence diagram and an image are generated through the diagram. We expect consistent image generation using the same image element asset through the proposed mechanism.