We've been using Pig extensively for our MR queries and we're very happy with it. While i haven't used Cascading, i do like the pipelining approach of Pig more than the SQL-influence method of Hive. It lends itself better for meeting our needs.

Testing is a good point. If you're running Pig through their APIs it is definitely easier to test than command-line running scripts. We've written test code that reads and runs pig scripts through the API using fixed sample data (stored in HDFS for easy access), read the results, and compare it to expected results (also stored in HDFS). Honestly, you don't need too much input data to prove the correctness of the query.

Remember that Pig also supports placeholders in your scripts so you that you can set them in run-time to define input/output paths, etc. This makes testing easier.

Dependencies can also be stored in HDFS which makes it simple to run your scripts w/o the need to distribute jars around.