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A design science research approach to Large Language Model-Based Agents for Requirements Specification (LLMBA4RS) in low-code applications

Cristian Rotar & Qingyu Zhang

Requirements Engineering2025https://doi.org/10.1007/s00766-025-00450-9article
AJG 2
Weight
0.50

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https://doi.org/https://doi.org/10.1007/s00766-025-00450-9

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@article{cristian2025,
  title        = {{A design science research approach to Large Language Model-Based Agents for Requirements Specification (LLMBA4RS) in low-code applications}},
  author       = {Cristian Rotar & Qingyu Zhang},
  journal      = {Requirements Engineering},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s00766-025-00450-9},
}

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A design science research approach to Large Language Model-Based Agents for Requirements Specification (LLMBA4RS) in low-code applications

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.