Generating Sequence Diagram from Natural Language Requirements

Jahan, Munima; Abad, Zahra Shakeri Hossein; Far, Behrouz H.

doi:10.1109/rew53955.2021.00012

Cited by 8 publications

(1 citation statement)

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“…Jahan et al [4] recognized the importance of automation in behavior modeling and proposed an automated approach for constructing SD (System Design) from natural language-written use case scenarios to bridge some of the gaps in the literature. Limaylla-Lunarejo et al [6] applied machine learning algorithms combined with natural language processing to classify software requirements into functional and non-functional categories. Koscinski et al [7] automated the formalization of NL (Natural Language) requirements by using IE (Information Extraction) techniques to extract structured information from NL SysRS (Natural Language System Requirements) data.…”

Section: A Sequential Analysis For Requirement Classification and Wor...mentioning

confidence: 99%

Chatbot Program for Proposed Requirements in Korean Problem Specification Document

Baek,

Park,

Park

2023

IJACSA

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In software engineering, requirement analysis is a crucial task throughout the entire process and holds significant importance. However, factors contributing to the failure of requirement analysis include communication breakdowns, divergent interpretations of requirements, and inadequate execution of requirements. To address these issues, a proposed approach involves utilizing NLP machine learning within Korean requirement documents to generate knowledge-based data and deduce actors and actions using natural language processing knowledge-based information. Actors and actions derived are then structured into a hierarchy of sentences through clustering, establishing a conceptual hierarchy between sentences. This is transformed into ontology data, resulting in the ultimate requirement list. A chatbot system provides users with the derived system event list, generating requirement diagrams and specification documents. Users can refer to the chatbot system's outputs to extract requirements. In this paper, the feasibility of this approach is demonstrated by applying it to a case involving Korean-language requirements for course enrollment.

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Section: A Sequential Analysis For Requirement Classification and Wor...mentioning

confidence: 99%