The CUDD package provides functions to manipulate Binary Decision Diagrams (BDDs) [5,3], Algebraic Decision Diagrams (ADDs) [1], and Zero suppressed Decision Diagrams (ZDDs) [12]. BDDs are used to represent switch functions

Temporal logic model checking is an automatic technique for verifying finite-state concurrent systems. Specifications are expressed in a propositional temporal logic, and the concurrent system is modeled as a state-transition graph. An efficient search procedure is used to determine whether or not the state-transition graph satisfies the specification. When the technique was first developed ten years ago, it was only possible to handle concurrent systems with a few thousand states. In the last few years, however, the size of the concurrent systems that can be handled has increased dramatically. By representing transition relations and sets of states implicitly using binary decision diagrams, it is now possible to check concurrent systems with more than 10 120 states. In this paper we describe in detail how the new implementation works and

Ordered Binary Decision Diagrams (OBDDs) have found widespread use in CAD applications such as formal verification, logic synthesis, and test generation. OBDDs represent Boolean functions in a form that is both canonical and compact for many practical cases. They can be generated and manipulated by efficient graph algorithms. Researchers have found that many tasks can be expressed as series of operations on Boolean functions, making them candidates for OBDD-based methods. The success of OBDDs has inspired efforts to improve their efficiency and to expand their range of applicability. Techniques have been discovered to make the representation more compact and to represent other classes of functions. This has led to improved performance on existing OBDD applications, as well as enabled new classes of problems to be solved. This paper provides an overview of the state of the art in graph-based function representations. We focus on several recent advances of particular importance for forma...

Binary Moment Diagrams (BMDs) provide a canonical representations for linear functions similar to the way Binary Decision Diagrams (BDDs) represent Boolean functions. Within the class of linear functions, we can embed arbitary functions from Boolean variables to real, rational, or integer values. BMDs can thus model the functionality of data path circuits operating over word level data. Many important functions, including integer multiplication, that cannot be represented efficiently at the bit level with BDDs have simple representations at the word level with BMDs. Furthermore, BMDs can represent Boolean functions with around the same complexity as BDDs. We propose

We compare SAT-checkers and decision diagrams on the evaluation of Boolean formulas produced in the formal verification of both correct and buggy versions of superscalar and VLIW microprocessors. We identify one SAT-checker that significantly outperforms the rest. We evaluate ways to enhance its performance by variations in the generation of the Boolean correctness formulas. We reassess optimizations previously used to speed up the formal verification and probe future challenges.

RuleBase is a formal verification tool, developed by the IBM Haifa Research Laboratory. It is the result of three years of experience in practical formal verification of hardware which, we believe, has been a key factor in bringing the tool to its current level of maturity. We present the tool, including several unique features, and summarize our usage experience.

Software components for embedded reactive real-time applications must satisfy tight code size and runtime constraints. Cooperating finite state machines provide a convenient intermediate format for embedded system co-synthesis, between high-level specification languages and software or hardware implementations. We propose a software generation methodology that takes advantage of a restricted class of specifications and allows for tight control over the implementation cost. The methodology exploits several techniques from the domain of Boolean function optimization. We also describe how the simplified control/data-flow graph used as an intermediate representation can be used to accurately estimate the size and timing cost of the final executable code.

Knowing that some variables are symmetric in a function has numerous applications; in particular, it can help produce better variable orders for Binary Decision Diagrams (BDDs) and related data structures (e.g., Algebraic Decision Diagrams). It has been observed that there often exists an optimum order for a BDD wherein symmetric variables are contiguous. We propose a new algorithm for the detection of symmetries, based on dynamic reordering, and we study its interaction with the reordering algorithm itself. We show that combining sifting with an efficient symmetry check for contiguous variables results in the fastest symmetry detection algorithm reported to date and produces better variable orders for many BDDs. The overhead on the sifting algorithm is negligible. 1

Binary Decision Diagrams (BDDs) have gained high attention in the context of design and verification of digital circuits. They have successfully been employed to encode very large state spaces in an efficient, symbolic way. Multi terminal BDDs (MTBDDs) are generalisations of BDDs from Boolean values to values of any finite domain. In this paper, we investigate the applicability of MTBDDs to the symbolic representation of continuous time Markov chains, derived from high-level formalisms, such as queueing networks or process algebras. Based on this data structure, we discuss iterative solution algorithms to compute the steady-state probability vector that work in a completely symbolic way. We highlight a number of lessons learned, using a set of small examples.

This paper presents a new data structure called Boolean Expression Diagrams (BEDs) for representing and manipulating Boolean functions. BEDs are a generalization of Binary Decision Diagrams (BDDs) which can represent any Boolean circuit in linear space and still maintain many of the desirable properties of BDDs. Two algorithms are described for transforming a BED into a reduced ordered BDD. One is a generalized version of the BDD apply-operator while the other can exploit the structural information of the Boolean expression. This ability is demonstrated by verifying that two di erent circuit implementations of a 16-bit multiplier implement the same Boolean function. Using BEDs, this veri cation problem is solved in less than a second, while using standard BDD techniques this problem is infeasible. Generally, BEDs are useful in applications, for example tautology checking, where the end-result as a reduced ordered BDD is small.