ChatGPT: A Study on its Utility for Ubiquitous Software Engineering Tasks
May 26, 2023 Β· Declared Dead Β· π arXiv.org
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Authors
Giriprasad Sridhara, Ranjani H. G., Sourav Mazumdar
arXiv ID
2305.16837
Category
cs.SE: Software Engineering
Cross-listed
cs.AI,
cs.LG
Citations
51
Venue
arXiv.org
Last Checked
4 months ago
Abstract
ChatGPT (Chat Generative Pre-trained Transformer) is a chatbot launched by OpenAI on November 30, 2022. OpenAI's GPT-3 family of large language models serve as the foundation for ChatGPT. ChatGPT is fine-tuned with both supervised and reinforcement learning techniques and has received widespread attention for its articulate responses across diverse domains of knowledge. In this study, we explore how ChatGPT can be used to help with common software engineering tasks. Many of the ubiquitous tasks covering the breadth of software engineering such as ambiguity resolution in software requirements, method name suggestion, test case prioritization, code review, log summarization can potentially be performed using ChatGPT. In this study, we explore fifteen common software engineering tasks using ChatGPT. We juxtapose and analyze ChatGPT's answers with the respective state of the art outputs (where available) and/or human expert ground truth. Our experiments suggest that for many tasks, ChatGPT does perform credibly and the response from it is detailed and often better than the human expert output or the state of the art output. However, for a few other tasks, ChatGPT in its present form provides incorrect answers and hence is not suited for such tasks.
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