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Building Traceability Between Functional Requirements and Component Architecture Elements in Embedded Software Using Structured Featuresoa mark
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Publication Year
2024-12-01
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Citation
Applied Sciences (Switzerland), Vol.14
Keyword
component architectureembedded softwarefunctional requirementrequirements traceabilitystructured feature
Mesh Keyword
Component architecturesCritical domainEmbedded-systemFunctional componentsFunctional requirementMedical DevicesQuality attributesRequirements architecturesRequirements traceabilityStructured feature
All Science Classification Codes (ASJC)
Materials Science (all)InstrumentationEngineering (all)Process Chemistry and TechnologyComputer Science ApplicationsFluid Flow and Transfer Processes
Abstract
In embedded software for critical domains such as medical devices and defense, requirement traceability is essential for ensuring quality attributes. Standards and regulations mandate traceability between requirements and artifacts such as design elements and code. However, existing methods often overlook the hardware-dependent nature of embedded systems or conduct traceability retroactively, which may affect consistency. This study introduces a structured feature-based approach to component architecture design, bridging the gap between requirements and design to ensure traceability. The structured feature model supports traceability between functional requirements, software components, and hardware elements in embedded systems. A case study demonstrates that structured features can effectively map the requirements to design artifacts, helping to visualize relationships through a traceability matrix. Although the process is manual, structured features improve efficiency in the early stages of design and create traceable links between requirements and architectural elements.
ISSN
2076-3417
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34662
DOI
https://doi.org/10.3390/app142310796
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Type
Article
Funding
Seok-Won Lee\\u2019s work was supported by the BK21 FOUR program of the National Research Foundation of Korea funded by the Ministry of Education (NRF5199991014091) and the Institute of Information& communications Technology Planning & Evaluation (IITP) under the Artificial Intelligence Convergence Innovation Human Resources Development (IITP-2024-RS-2023-00255968) grant funded by the Korea government (MSIT).
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Lee, Seok-Won Image
Lee, Seok-Won이석원
Department of Software and Computer Engineering
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