Algorithms for functional (and other) dependency discovery
FD discovery addresses the following problem: given a dataset (a table), find all functional dependencies that hold in this dataset. Such regularities in data are of interest to applied researchers since they allow to formulate hypotheses and even draw conclusions regarding the data. Here, the main challenge is that such discovery is a very computationally expensive problem. Even a relatively small dataset may require several days of runtime. In this project we focus on improving such algorithms and their components.