I have run into an interesting issue with Bibdesk (1.8.16) that I had not 
encountered before. I have a .bib file that has entries like the following. The 
relevant part of this is the @inproceedings{icde22_Wang:2022aa line. When I 
copy them into my master Bibdesk library, it loses the “icde22_” and shows the 
Cite Key as "Wang:2022aa”. If I manually go in and update the Cite key, it 
shows the “icde22_” but not when I copy/paste it the bibtex record. Any ideas 
as to why this might be happening would be appreciated. In the meantime, I’ll 
try on another machine to see if it something with my setup.

@inproceedings{icde22_Wang:2022aa,
        author = {Wang, Haibo and Ma, Chaoyi and Chen, Shigang and Wang, 
Yuanda},
        booktitle = ICDE22,
        date-added = {2023-05-16 09:11:03 -0400},
        date-modified = {2023-05-16 09:11:04 -0400},
        doi = {10.1109/ICDE53745.2022.00005},
        issn = {2375-026X},
        keywords = {ICDE22,Measurement;Estimation error;Art;Social networking 
(online);Throughput;Data engineering;Servers;Cardinality 
Estimationi;Online;Self morphing;Bitmap},
        pages = {1--13},
        title = {Online Cardinality Estimation by Self-morphing Bitmaps},
        year = {2022},
        abstract = {Estimating the cardinality of a data stream is a 
fundamental problem underlying numerous applications such as traffic monitoring 
in a network or a datacenter, popularity tracking on social media, and cache 
optimization in proxy servers. Existing solutions suffer from high 
processing/query overhead or memory in-efficiency, which prevents them from 
operating online for data streams with very high arrival rates. This paper 
takes a new solution path different from the prior art and proposes a 
self-morphing bitmap, which combines operational simplicity with structural 
dynamics, allowing the bitmap to be morphed in a series of steps with an 
evolving sampling probability that automatically adapts to different stream 
sizes. We evaluate the self-morphing bitmap theoretically and experimentally. 
The results demonstrate that it significantly outperforms the prior art.},
        bdsk-url-1 = {https://doi.org/10.1109/ICDE53745.2022.00005}}


==Tamer
--
M. Tamer Özsu
University of Waterloo
Cheriton School of Computer Science
https://cs.uwaterloo.ca/~tozsu 



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