Prompted Software Engineering in the Era of AI Models
Dae-Kyoo Kim

TL;DR
This paper presents prompted software engineering (PSE), a novel approach that uses prompt engineering to improve AI-assisted software development, aiming to produce high-quality software efficiently while reducing resource use.
Contribution
It introduces the concept of prompted software engineering (PSE) and discusses how to construct effective prompts throughout the software development cycle.
Findings
PSE enables automation of tedious tasks in software development.
Effective prompts improve AI response accuracy and relevance.
PSE reduces resource consumption in software projects.
Abstract
This paper introduces prompted software engineering (PSE), which integrates prompt engineering to build effective prompts for language-based AI models, to enhance the software development process. PSE enables the use of AI models in software development to produce high-quality software with fewer resources, automating tedious tasks and allowing developers to focus on more innovative aspects. However, effective prompts are necessary to guide software development in generating accurate, relevant, and useful responses, while mitigating risks of misleading outputs. This paper describes how productive prompts should be built throughout the software development cycle.
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Software Engineering Research
