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Natural Language Processing to assess structure and complexity of system requirements

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A2IA87KAL" target="_blank" >RIV/00216208:11320/25:2IA87KAL - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203705781&doi=10.1002%2fsys.21784&partnerID=40&md5=8e43b167c3ac54f6b439d3786d41b3d1" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203705781&doi=10.1002%2fsys.21784&partnerID=40&md5=8e43b167c3ac54f6b439d3786d41b3d1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/sys.21784" target="_blank" >10.1002/sys.21784</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Natural Language Processing to assess structure and complexity of system requirements

  • Original language description

    The development process of a system is shaped by numerous variables that influence its progress and outcome. As a result, complexity can increase throughout the development process, potentially leading to negative consequences, which makes the management of complexity critical. Most development processes begin with the definition of needs and requirements. In this paper, the authors present a novel approach that enables the automated extraction of structure from requirements specifications. The approach uses Natural Language Processing to elicit three structural layers from a set of requirements, which are subsequently analyzed using metrics to assess complexity. In a case study, the approach is demonstrated using a set of 79 requirements, within which 246 individual entities are identified. These entities and the requirements are structured and analyzed using network density and spectral entropy. The metrics allow for interpretation and insight generation, such as identifying an increase in the number of potentially problematic loops. The approach achieved a detection and structural accuracy of over 98% in the given case study and is planned to be expanded with future cases. © 2024 Wiley Periodicals LLC.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Systems Engineering

  • ISSN

    1098-1241

  • e-ISSN

  • Volume of the periodical

    2024

  • Issue of the periodical within the volume

    2024

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    12

  • Pages from-to

    1-12

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85203705781