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Graphbased algorithms for Boolean function manipulation
 IEEE TRANSACTIONS ON COMPUTERS
, 1986
"... In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions on th ..."
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Cited by 3509 (47 self)
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In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions on the ordering of decision variables in the graph. Although a function requires, in the worst case, a graph of size exponential in the number of arguments, many of the functions encountered in typical applications have a more reasonable representation. Our algorithms have time complexity proportional to the sizes of the graphs being operated on, and hence are quite efficient as long as the graphs do not grow too large. We present experimental results from applying these algorithms to problems in logic design verification that demonstrate the practicality of our approach.
Formal Verification by Symbolic Evaluation of PartiallyOrdered Trajectories
 Formal Methods in System Design
, 1993
"... Symbolic trajectory evaluation provides a means to formally verify properties of a sequential system by a modified form of symbolic simulation. The desired system properties are expressed in a notation combining Boolean expressions and the temporal logic "nexttime" operator. In its sim ..."
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Cited by 104 (24 self)
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Symbolic trajectory evaluation provides a means to formally verify properties of a sequential system by a modified form of symbolic simulation. The desired system properties are expressed in a notation combining Boolean expressions and the temporal logic "nexttime" operator. In its simplest form, each property is expressed as an assertion [A =) C], where the antecedent A expresses some assumed conditions on the system state over a bounded time period, and the consequent C expresses conditions that should result. A generalization allows simple invariants to be established and proven automatically. The verifier operates on system models in which the state space is ordered by "information content". By suitable restrictions to the specification notation, we guarantee that for every trajectory formula, there is a unique weakest state trajectory that satisfies it. Therefore, we can verify an assertion [A =) C] by simulating the system over the weakest trajectory for A and testing...
A Methodology for Hardware Verification Based on Logic Simulation
 Journal of the ACM
, 1991
"... A logic simulator can prove the correctness of a digital circuit if it can be shown that only circuits fulfilling the system specification will produce a particular response to a sequence of simulation commands. This style of verification has advantages over other proof methods in being readily a ..."
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Cited by 37 (4 self)
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A logic simulator can prove the correctness of a digital circuit if it can be shown that only circuits fulfilling the system specification will produce a particular response to a sequence of simulation commands. This style of verification has advantages over other proof methods in being readily automated and requiring less attention on the part of the user to the lowlevel details of the design. It has advantages over other approaches to simulation in providing more reliable results, often at a comparable cost.
Formal Verification of Digital Circuits Using Symbolic Ternary System Models
"... Ternary system modeling involves extending the traditional set of binary values f0; 1g with a third value X indicating an unknown or indeterminate condition. By making this extension, we can model a wider range of circuit phenomena. We can also efficiently verify sequential circuits in which the ..."
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Cited by 26 (5 self)
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Ternary system modeling involves extending the traditional set of binary values f0; 1g with a third value X indicating an unknown or indeterminate condition. By making this extension, we can model a wider range of circuit phenomena. We can also efficiently verify sequential circuits in which the effect of a given operation depends on only a subset of the total system state.
Formal Verification of Memory Circuits by SwitchLevel Simulation
 IEEE Transactions on ComputerAided Design of Integrated Circuits and Systems
, 1991
"... A logic simulator can prove the correctness of a digital circuit if it can be shown that only circuits implementing the system specification will produce a particular response to a sequence of simulation commands. Threevalued modeling, where the third state indicates a signal with unknown digital ..."
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Cited by 11 (5 self)
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A logic simulator can prove the correctness of a digital circuit if it can be shown that only circuits implementing the system specification will produce a particular response to a sequence of simulation commands. Threevalued modeling, where the third state indicates a signal with unknown digital value, can greatly reduce the number of patterns that need to be simulated for complete verification. As an extreme case, an bit randomaccess memory (RAM) can be verified by simulating just log patterns. This approach to verification is fast, requires minimal attention on the part of the user to the circuit details, and can utilize more sophisticated circuit models than other approaches to formal verification. The technique has been applied to a CMOS static RAM design using the COSMOS switchlevel simulator. By simulating many patterns in parallel, a massivelyparallel computer can verify a 4K RAM in under 6 minutes. 1.
Digital Circuit Verification using PartiallyOrdered State Models
 In International Symposium on MultiValued Logic
, 1994
"... Many aspects of digital circuit operation can be efficiently verified by simulating circuit operation over "weakened" state values. This technique has long been practiced with logic simulators, using the value X to indicate a signal that could be either 0 or 1. This concept can be formally ..."
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Cited by 4 (1 self)
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Many aspects of digital circuit operation can be efficiently verified by simulating circuit operation over "weakened" state values. This technique has long been practiced with logic simulators, using the value X to indicate a signal that could be either 0 or 1. This concept can be formally extended to a wider class of circuit models and signal values, yielding latticestructured state domains. For more precise modeling of circuit operation, these values can be encoded in binary and hence represented symbolically as Ordered Binary Decision Diagrams. The net result is a tool for formal verification that can apply a hybrid of symbolic and partiallyordered evaluation.
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"... A new placement algorithm for general cell assemblies is presented which combines the ideas of polar graph representation and mincut placement. First a detailed description of the initial placement procedure is given, then the various methods for placement improvement (rotation, squeezing, reflecti ..."
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A new placement algorithm for general cell assemblies is presented which combines the ideas of polar graph representation and mincut placement. First a detailed description of the initial placement procedure is given, then the various methods for placement improvement (rotation, squeezing, reflecting) and global routing are discussed. A sample circuit is used to demonstrate the performance of the algorithms. Results are shown to