The chase is a simple fixed-point algorithm testing and enforcing implication of data dependencies in database systems.
It plays important roles in database theory as well as in practice.
It is used, directly or indirectly, on an everyday basis by people who design databases, and it is used in commercial systems to reason about the consistency and correctness of a data design.
[citation needed] New applications of the chase in meta-data management and data exchange are still being discovered.
The chase has its origins in two seminal papers of 1979, one by Alfred V. Aho, Catriel Beeri, and Jeffrey D. Ullman[1] and the other by David Maier, Alberto O. Mendelzon, and Yehoshua Sagiv.
[2] In its simplest application the chase is used for testing whether the projection of a relation schema constrained by some functional dependencies onto a given decomposition can be recovered by rejoining the projections.
If tuples in R are represented as t1, ..., tk, the join of the projections of each ti should agree with t on
There exist implementations of the chase algorithm,[3] some of them are also open-source.
[4] Let R(A, B, C, D) be a relation schema known to obey the set of functional dependencies F = {A→B, B→C, CD→A}.
Determining whether this decomposition is lossless can be done by performing a chase as shown below.
To perform the chase test, first decompose all FDs in F so each FD has a single attribute on the right hand side of the "arrow".
(In this example, F remains unchanged because all of its FDs already have a single attribute on the right hand side: F = {A→B, B→C, CD→A}.)
When equating two symbols, if one of them is unsubscripted, make the other be the same so that the final tableau can have a row that is exactly the same as t = (a, b, c, d).