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Making sense of revision-control systems
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All revision-control systems come with complicated sets of trade-offs. How do you find the best match between tool and team?
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“Although the underlying LLM, GPT-4, supports multiple languages [69], our study focused on English writing tasks.”
From ABScribe: Rapid Exploration & Organization of Multiple Writing Variations in Human-AI Co-Writing Tasks using Large Language Models (2024) · cites this paper as [69]
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Metadata
- Authors
- O'Sullivan, B.
- Affiliations
- San Francisco
- Venue
- Communications of the ACM
- Published
- 2009-09
- Volume
- 52
- Issue
- 9
- Pages
- 56-62
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2147397672
- Cited by
- 61
- References
- 0
- Citations by year
- 2024: 2 · 2023: 3 · 2020: 1 · 2019: 2 · 2018: 4 · 2017: 4 · 2016: 6 · 2015: 6 · 2014: 5 · 2013: 6 · 2012: 7
- FWCI
- 19.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Communications of the ACM (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
- Keywords
- version control, software development teams, tool selection, trade-offs
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
