Investigating Explainability of Generative AI for Code through Scenario-based Design

Research article (27th International Conference on Intelligent User Interfaces, 2022) · cited 208× · AI/ML
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Investigating Explainability of Generative AI for Code through Scenario-based Design

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Investigating Explainability of Generative AI for Code through Scenario-based Design is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Investigating Explainability of Generative AI for Code through Scenario-based Design. Retrieved May 24, 2026, from https://4ort.xyz/entity/investigating-explainability-of-generative-ai-for-code-through-scenario-based-design
MLA “Investigating Explainability of Generative AI for Code through Scenario-based Design.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/investigating-explainability-of-generative-ai-for-code-through-scenario-based-design.
BibTeX @misc{4ortxyz_investigating-explainability-of-generative-ai-for-code-through-scenario-based-design_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Investigating Explainability of Generative AI for Code through Scenario-based Design}}, year = {2026}, url = {https://4ort.xyz/entity/investigating-explainability-of-generative-ai-for-code-through-scenario-based-design}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Investigating Explainability of Generative AI for Code through Scenario-based Design — https://4ort.xyz/entity/investigating-explainability-of-generative-ai-for-code-through-scenario-based-design (retrieved 2026-05-24)

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