The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
What Do Developers Want From AI?
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In the citing paper
“D'Angelo et al. [40] and Hou and Jansen [68] highlight the roles of control, expectation management, and reputation in shaping trust.”
From What Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI (2025) · cites this paper as [40]
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Citations
Cites
Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions
Pearce, H., Ahmad, B., Tan, B., Dolan-Gavitt, B., & Karri, R. (2022) · 2022 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp46214.2022.9833571 · Cited by 476
Do Users Write More Insecure Code with AI Assistants?
Perry, N., Srivastava, M., Kumar, D., & Boneh, D. (2023) · Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/3576915.3623157 · Cited by 259
AI in Software Engineering at Facebook
Bader, J., Seohyun Kim, S., Sifei Luan, F., Chandra, S., & Meijer, E. (2021) · IEEE Software · doi:10.1109/ms.2021.3061664 · Cited by 16
Self-citationDo Users Write More Insecure Code with AI Assistants?
Perry, N., Srivastava, M., Kumar, D., & Boneh, D. (2022) · arXiv
Research works printed but not linked: 9
- 2024, Early LLM-based tools for enterprise information workers likely provide meaningful boosts to productivity
- 2011, Henry Ford, innovation, and that Faster Horse quote
- 2017, User research and design: Three old chestnuts cracked
- 2024, A developers second brain: Reducing complexity through partnership with AI
- 2024, The history of car technology
- 2024, Transformer: A novel neural network architecture for language understanding
- 2024, AI-assisted application development
- 2024, Resolving code review comments with ML
- 10.1145/1455567.1455599 · DOI
Cited by
How much does AI impact development speed? An enterprise-based randomized controlled trial
Paradis, E., Grey, K., Madison, Q., Nam, D., Macvean, A., Meimand, V., Zhang, N., Ferrari-Church, B., & Chandra, S. (2024) · arXiv · doi:10.48550/arxiv.2410.12944 · Cited by 20
Self-citationHow Much Does AI Impact Development Speed? an Enterprise-Based Randomized Controlled Trial
Paradis, E., Grey, K., Madison, Q., Nam, D., Macvean, A., Meimand, V., Zhang, N., Ferrari-Church, B., & Chandra, S. (2025) · 2025 IEEE/ACM 47th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) · doi:10.1109/icse-seip66354.2025.00060 · Cited by 20
Self-citationWhat Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI
Choudhuri, R., Trinkenreich, B., Pandita, R., Kalliamvakou, E., Steinmacher, I., Gerosa, M., Sanchez, C., & Sarma, A. (2025) · arXiv · doi:10.48550/arxiv.2505.17418 · Cited by 14
Metadata
- Authors
- D’Angelo, S., Murillo, A., Chandra, S., & Macvean, A.
- Affiliations
- Engineering Productivity Research Team, Google, Auckland, New Zealand
- Core Developer Team, Google, Munich, Germany
- Developer AI Team, Google, Sunnyvale, CA, USA
- Developer Organization, Google, Seattle, WA, USA
- Venue
- IEEE Software
- Published
- 2024-05
- Volume
- 41
- Issue
- 3
- Pages
- 11-15
- ISSN
- 0740-7459
- 1937-4194
- Cited by
- 6
- References
- 4
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
