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https://issues.apache.org/jira/browse/CASSANDRA-15537?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17203946#comment-17203946
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Paulo Motta commented on CASSANDRA-15537:
-----------------------------------------

Hi [~yifanc], do you have any update on the diff tests? Is work of this task 
composed solely of the tests you are running or can it be split into subtasks 
so others can maybe help?

For context, I'm asking this to check the status of the 4.0 quality epic as 
part of this [this 
discussion|https://www.mail-archive.com/dev@cassandra.apache.org/msg15881.html] 
on the mailing list.

> 4.0 quality testing: Local Read/Write Path: Upgrade and Diff Test
> -----------------------------------------------------------------
>
>                 Key: CASSANDRA-15537
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-15537
>             Project: Cassandra
>          Issue Type: Task
>          Components: Test/dtest/java, Test/dtest/python
>            Reporter: Josh McKenzie
>            Assignee: Yifan Cai
>            Priority: Normal
>             Fix For: 4.0-beta
>
>
> Reference [doc from 
> NGCC|https://docs.google.com/document/d/1uhUOp7wpE9ZXNDgxoCZHejHt5SO4Qw1dArZqqsJccyQ/edit#]
>  for context.
> Execution of upgrade and diff tests via cassandra-diff have proven to be one 
> of the most effective approaches toward identifying issues with the local 
> read/write path. These include instances of data loss, data corruption, data 
> resurrection, incorrect responses to queries, incomplete responses, and 
> others. Upgrade and diff tests can be executed concurrent with fault 
> injection (such as host or network failure); as well as during mixed-version 
> scenarios (such as upgrading half of the instances in a cluster, and running 
> upgradesstables on only half of the upgraded instances).
> Upgrade and diff tests are expected to continue through the release cycle, 
> and are a great way for contributors to gain confidence in the correctness of 
> the database under their own workloads.



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