  In the context of test case based automated program repair (APR), the
research community call the patches that pass all the test cases but fail to
actually fix the bug test case overfitted patches. Currently, overfitted
patches has to be manually inspected by the users. Being a labor intensive
activity that hinders widespread adoption of APR tools, automatic validation of
APR-generated patches has been the topic of research in recent years. In this
paper, we point out the limitations of the existing techniques/methodologies
that call for further research, and introduce two promising directions toward
effective automatic patch validation: (1) motivated by the relative
effectiveness of anti-patterns, we propose to use statistical techniques to
avoid the uncomputability of applying some of the anti-pattern rules and
automate the technique. Our results show that we achieve at least 57%
precision. (2) We present a proposal for a semi-automatic technique that helps
the programmers in finding properties of the patched methods and stress testing
the patches based on those properties so as to filter out overfitted ones as
many as possible.
