• International journal of advanced smart convergence
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• v.13 no.1
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• pp.92-98
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• 2024

The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

• 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.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.2
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• pp.43-65
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• 2013

In this work, we first introduce two main approaches to writing requirements and then propose a method based on Natural Language Processing to improve requirement authoring and the overall coherence, cohesion and organization of requirement documents. We investigate the structure of requirement kernels, and then the discourse structure associated with those kernels. This will then enable the system to accurately extract requirements and their related contexts from texts (called requirement mining). Finally, we relate a first experimentation on requirement mining based on texts from seven companies. An evaluation that compares those results with manually annotated corpora of documents is given to conclude.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.218-226
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• 2023

In Korea, we still use function point based cost estimations for software size and cost of a project. The current problem is that we make difficultly calculating function points with requirements and also have less accurate. That is, it is difficult for non-experts to analyze requirements and calculate function point values with them, and even experts often derive different function points. In addition, all stakeholders strongly make the validity and accuracy of the function point values of the project before /after the development is completed. There are methods for performing function point analysis using source code [1][2][3][4] and some researchers [5][6][7] attempt empirical verification of function points about the estimated cost. There is no research on automatic cost validation with source code after the final development is completed. In this paper, we propose automatically how to calculate Function Points based on natural language requirements before development and prove FP calculation based on the final source code after development. We expect validation by comparing the function scores calculated by forward engineering and reverse engineering methods.

• 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.

• Nuclear Engineering and Technology
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• v.36 no.4
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• pp.295-303
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• 2004

Software inspection is widely believed to be an effective method for software verification and validation (V&V). However, software inspection is labor-intensive and, since it uses little technology, software inspection is viewed upon as unsuitable for a more technology-oriented development environment. Nevertheless, software inspection is gaining in popularity. KAIST Nuclear I&C and Information Engineering Laboratory (NICIEL) has developed software management and inspection support tools, collectively named "SIS-RT. "SIS-RT is designed to partially automate the software inspection processes. SIS-RT supports the analyses of traceability between a given set of specification documents. To make SIS-RT compatible for documents written in Korean, certain techniques in natural language processing have been studied [9]. Among the techniques considered, case grammar is most suitable for analyses of the Korean language [3]. In this paper, we propose a methodology that uses a case grammar approach to analyze the traceability between documents written in Korean. A discussion regarding some examples of such an analysis will follow.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.85-91
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• 2024

Currently, generative artificial intelligence is a hot topic around the world. Generative artificial intelligence creates various images, art, video clips, advertisements, etc. The problem is that it is very difficult to verify the internal work of artificial intelligence. As a requirements engineer, I attempt to create a toon image by applying linguistic mechanisms to the current issue. This is combined with the UML object model through the semantic role analysis technique of linguists Chomsky and Fillmore. Then, the derived properties are linked to the toon creation template. This is to ensure productivity based on reusability rather than creativity in toon engineering. In the future, we plan to increase toon image productivity by incorporating software development processes and reusability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2718-2731
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• 2023

This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.1
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• pp.19-27
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• 2018

For the purpose of technology planning and R&D strategy, this research developed a methodology for deriving technical information based on stakeholder requirements using natural language processing technology. The requirements are decomposed into semantic information based on grammar rules, and then the requirement information based technology information can be derived by linking with the three technical information extracted from the patent.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.