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  1. ; ; ; ; (, 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC))
    Full Text Available 
  2. ; ; ; ; ; (, NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing Systems)
    Accepted Manuscript Full Text Available
  3. ; ; ; ; ; ; ; ; (, ACM)
  4. ; ; ; ; (, 2023 the 44th IEEE Symposium on Security and Privacy (SP))
    Full Text Available 
  5. ; ; ; ; (, Proceedings of the 38th Annual Computer Security Applications Conference (ACSAC))
    Full Text Available 
  6. ; ; ; ; ; ; ; ; ; ; et al (, 2023 60th ACM/IEEE Design Automation Conference (DAC))
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  7. ; ; ; ; ; (, 13th Annual Conference on Innovative Data Systems Research (CIDR ’23))
  8. ; ; ; ; ; (, 13th Annual Conference on Innovative Data Systems Research (CIDR ’23). January 8-11, 2023, Amsterdam, The Netherlands.)
    Many database applications execute transactions under a weaker isolation level, such as READ COMMITTED. This often leads to concurrency bugs that look like race conditions in multi-threaded programs. While this problem is well known, philosophies of how to address this problem vary a lot, ranging from making a SERIALIZABLE database faster to living with weaker isolation and the consequence of concurrency bugs. This paper studies the consequences, root causes, and how developers fix 93 real-world concurrency bugs in database applications. We observe that, on the one hand, developers still prefer preventing these bugs from happening. On the other hand, database systems are not providing sufficient support for this task, so developers often fix these bugs using ad-hoc solutions, which are often complicated and not fully correct. We further discuss research opportunities to improve concurrency control in database implementations. 
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    Accepted Manuscript Full Text Available
  9. ; ; ; ; ; (, 13th Annual Conference on Innovative Data Systems Research (CIDR ’23). January 8-11, 2023, Amsterdam, The Netherlands.)
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ; ; ; (, IEEE Big Data)
    Full Text Available