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The importance of visual modelling languages in generative software engineering

arXiv 2411.17976 ↗First posted 27 Nov 2024cs.SE cs.AIcited by 1

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Abstract (arXiv)

Multimodal GPTs represent a watershed in the interplay between Software Engineering and Generative Artificial Intelligence. GPT-4 accepts image and text inputs, rather than simply natural language. We investigate relevant use cases stemming from these enhanced capabilities of GPT-4. To the best of our knowledge, no other work has investigated similar use cases involving Software Engineering tasks carried out via multimodal GPTs prompted with a mix of diagrams and natural language.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 25 of its 37 references that are in the map. First posted on arXiv 27 Nov 2024.

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25 of 37 references.

References · 25

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13 more
  1. 2022PromptSource: An Integrated Development Environment and Repository for Natural Language Promptscited by 289
  2. 2021Generated Knowledge Prompting for Commonsense Reasoningcited by 214
  3. 2023ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generationcited by 168
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  5. 2023Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)cited by 72
  6. 2023ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Designcited by 66
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  8. 2023Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programmingcited by 20
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  11. 2024From Image to UML: First Results of Image Based UML Diagram Generation Using LLMscited by 11
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