February, 2012

This semester, we have been working on becoming familiar with SAT solvers and methods. In learning how SAT solvers work, we have begun to explore the parallels between SAT solvers and CSP solvers, which can be used to solve the same problems but use different modeling techniques and search methodologies.

In order to delve into SAT, we have been exploring a well-known solver called MiniSAT (http://minisat.se). In order to understand how MiniSAT works, we traced the functions of the program and printed out the assumption and trail at each decision level. In order to parse the MiniSAT code more effectively, we read a paper by Niklas Eén and Niklas Sörensson, the creators of MiniSAT. The paper, titled “An Extensible SAT-solver”, explains the basic functionalities of the solver’s classes and methods as well as an overview of its core algorithms. It has been immensely helpful in understanding how MiniSAT propagates, learns conflict clauses and traverses the search space.

Recently, we have been working on a visualization of the MiniSAT search process. Using the dot graphing language, we can program MiniSAT to output dot code to a file, with each assumption represented as a node in a tree, and with backtracking being represented as separate branches of the tree. This exercise is very rewarding in that it provides a simple graphical interpretation of SAT solving. Once able to output dot code during the program’s runtime, we are working on storing information relevant to outputting the graphs nodes and branches into data structures that we can then store in our modified MiniSAT code. 

--Maggie