We have a new White Paper available:
Automatic Constraint Generation and Verification
Correctness is a key problem at every stage of data science projects: completing an entire analysis without a serious error at some stage is surprisingly hard. Even errors that reverse or completely invalidate the analysis can be hard to detect. Test-Driven Data Analysis (TDDA) attempts to identify, reduce, and aid correction of such errors. A core tool that we use in TDDA is Automatic Constraint Discovery and Verification, the focus of this paper.