2303.07839 (1).pdf- “ChatGPT: Revolutionizing Software Engineering Automation” – “Unleashing the Power of Large Language Models in Software Engineering” – “Improving Code Quality and Refactoring with ChatGPT” – “Accelerating Requirements Elicitation with ChatGPT” – “Enhancing Software Design and Rapid Prototyping using ChatGPT”

– Large language models (LLMs) like ChatGPT are being used for software engineering tasks.
– LLMs require prompts, which are natural language instructions, to perform tasks.
– This paper presents prompt patterns to solve common software engineering problems.
– Prompt patterns can improve code quality, refactoring, requirements elicitation, and software design.
– The paper provides a catalog of prompt patterns and explores their application in different software development phases.

– The paper mentions using large language models (LLMs) like ChatGPT.
– LLMs have the capability to generate synthetic data and simulate APIs.
– LLMs can help developers interact with and test APIs through simulation.
– LLMs can provide usage guidance and explain errors in the API.

– Prompt patterns can help reduce errors and mistakes in software engineering tasks.
– LLMs like ChatGPT have immense potential to automate software engineering tasks.
– Human involvement and expertise are necessary to effectively leverage LLMs.
– Close scrutiny is required to address the issue of confident but incorrect output.
– Further work is needed on prompt engineering for accurate and helpful output.
– Readers are encouraged to test the prompt patterns in their own domains.

– Paper presents prompt design techniques for software engineering using large language models (LLMs)
– Provides a catalog of patterns for software engineering problem-solving
– Finds prompt patterns for requirements elicitation, code quality, and more.

– Prompt patterns can help reduce errors and improve code quality.
– LLMs have immense potential for automating software engineering tasks.
– Human involvement and expertise are necessary to effectively leverage LLMs.
– Close scrutiny is required to address the issue of confident but incorrect output.
– Further work is needed on prompt engineering to ensure accurate and helpful output.

– Catalog of patterns for software engineering
– Prompt patterns for requirements elicitation, rapid prototyping, code quality, deployment, and testing.