Evaluating Privacy Questions From Stack Overflow: Can ChatGPT Compete?
| Autor: | Delile, Zack, Radel, Sean, Godinez, Joe, Engstrom, Garrett, Brucker, Theo, Young, Kenzie, Ghanavati, Sepideh |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | 2023 IEEE 31st International Requirements Engineering Conference Workshops (REW) |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/REW57809.2023.00048 |
| Popis: | Stack Overflow and other similar forums are used commonly by developers to seek answers for their software development as well as privacy-related concerns. Recently, ChatGPT has been used as an alternative to generate code or produce responses to developers' questions. In this paper, we aim to understand developers' privacy challenges by evaluating the types of privacy-related questions asked on Stack Overflow. We then conduct a comparative analysis between the accepted responses given by Stack Overflow users and the responses produced by ChatGPT for those extracted questions to identify if ChatGPT could serve as a viable alternative. Our results show that most privacy-related questions are related to choice/consent, aggregation, and identification. Furthermore, our findings illustrate that ChatGPT generates similarly correct responses for about 56% of questions, while for the rest of the responses, the answers from Stack Overflow are slightly more accurate than ChatGPT. Comment: Submitted to the 10th International Workshop on Evolving Security & Privacy Requirements Engineering (ESPRE'23) co-located with the 31st IEEE International Requirements Engineering Conference September 4-8, 2023, Leibniz Universit\"at, Hannover, Germany |
| Databáze: | arXiv |
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