This article explores innovative prompt design techniques to harness large language models (LLMs) like ChatGPT for software engineering. These techniques focus on addressing common challenges, such as decoupling code from third-party libraries and simulating APIs pre-implementation. The work categorizes prompt patterns by problem type, offering practical solutions to elevate requirements elicitation, prototyping, code quality, refactoring, and system design. By automating repetitive tasks, these patterns empower engineers to streamline workflows and achieve high-quality outcomes efficiently. This approach bridges research and practice, showcasing how LLMs can revolutionize traditional development processes, fostering smarter, more agile engineering solutions.
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Enhancing Software Engineering with Prompt Patterns for LLMs
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