In computer science, a binary decision diagram (BDD) or branching program is a data structure that is used to represent a Boolean function. On a more abstract level, BDDs can be considered as a compressed representation of sets or relations.

What can BDDs be used for? • Theorem (R. Bryant): If G, G’ are ROBDD’s of a Boolean function f with k inputs, using same variable ordering, then G and G’ are identical. Given a function with n inputs, one input ordering may require exponential # vertices in ROBDD, while other may be linear in size. Just two of them! ITE( I(x), T(x), E(x) ) = I(x) .

Due to these auspicious properties, the term BDD almost always refers to some minor variation of the ROBDD devised by Bryant. In this chapter, we will discuss how to construct and visualize ROBDDs using PyEDA.

Hey Comrades. In this video, I have explained in detail the construction of ROBDD. It is found in the MTech syllabus of Electronics specialization courses. I...

˃Each root and descendants form an ROBDD ˃Different roots can share subgraphs ˃Variable ordering same for all functions represented » Unique Table: a hash table ˃Every ROBDD node characterized by (v, f 1, f 0) + v : variable; f 1, f 0: ROBDD node pointers to 1-child and 0-child ˃Hash table: key = (v, f 1 1) ˃ 1

We are concerned only with Reduced Ordered Binary Decision Diagrams (ROBDD). Often, one refers to a ROBDD as simply a BDD for short, but there are also other types of BDDs. For us, BDD will always mean ROBDD.

Decision Diagram is a data structure for representing and manipulating boolean expressions. In its restrict form, called Reduced Ordered Binary Decision Diagram (ROBDD), its application became comprehensive for its canonical aspect and for allowing efficient manipulations. The package includes a sample - sample.queens.py.

ROBDDs are BDDs following a specified variable ordering and simplified/reduced using reduction rules. This is a very desirable property for determining formal equivalence. Two reduction rules exist for converting an OBDD into a ROBDD: exp = nodeLo. exp node = nodeLo. try: node = cache [key] except KeyError: node = Node (var, nodeLo, nodeHi)

Let Var be a finite set of Boolean variables and ℘ a variable ordering for Var. Then: How to reduce an OBDD? fstab(x, y) = (x1 ↔ y1) . . . f ∈ Eval(z1, . . . , z ) is symmetric if and only if. for each permutation (i1, . . . , ) of im (1, . . . , m) z1 ∨ z2 ∨ . . . (x1, . . . , x ) = 1 iff the number of variables x with value 1 is even feven n i.

As promised, here is the video on 2 examples of Binary Decision Diagram and ROBDD. I have explained each and every step of how to solve a BDD problem and als...