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This thesis describes research to implement a Bayesian belief network based expert system to solve a real-world diagnostic problem troubleshooting integrated circuit (IC) testing machines. Several models of the IC tester diagnostic problem were developed in belief networks, and one of these models was implemented using Symbolic Probabilistic Inference (SPI). The difficulties and advantages encountered in the process are described in this thesis. It was observed that modelling with interdependencies in belief networks simplified the knowledge engineering task for the IC tester diagnosis problem, by avoiding procedural knowledge and sticking just to diagnostic component's interdependencies. Several general model frameworks evolved through knowledge engineering to capture diagnostic expertise that facilitated expanding and modifying the networks. However, model implementation was restricted to a small portion of the modelling - contact resistance failures - because evaluation of the probability distributions could not be made fast enough to expand the code to a complete model with real-time diagnosis. Further research is recommended to create new methods, or refine existing methods, to speed evaluation of the models created in this research. If this can be done, more complete diagnosis can be achieved. / Graduation date: 1994

This dissertation combines formal verification techniques in an attempt to reduce the human effort required to verify large systems formally. One method to reduce the human effort required by formal verification is to modify general-purpose theorem proving techniques to increase the number of lemma instances considered automatically. Such a modification to the forward chaining proof technique within the ACL2 theorem prover is described. This dissertation identifies a decidable subclass of the ACL2 logic, the Subclass of Unrollable List Formulas in ACL2 (SUFLA). SUFLA is shown to be decidable, i.e., there exists an algorithm that decides whether any SUFLA formula is valid. Theorems from first-order logic can be proven through a methodology that combines interactive theorem proving with a fully-automated solver for SUFLA formulas. This methodology has been applied to the verification of components of the TRIPS processor, a prototype processor designed and fabricated by the University of Texas and IBM. Also, a fully-automated procedure for the Satisfiability Modulo Theory (SMT) of bit vectors is implemented by combining a solver for SUFLA formulas with the ACL2 theorem prover's general-purpose rewriting proof technique. A new methodology for combining theorem proving and model checking is presented, which uses a unique "black-box" formalization of hardware designs. This methodology has been used to combine the ACL2 theorem prover with IBM's SixthSense model checker and applied to the verification of a high-performance industrial multiplier design. A general-purpose mechanism has been created for adding external tools to a general-purpose theorem prover. This mechanism, implemented in the ACL2 theorem prover, is capable of supporting the combination of ACL2 with both SixthSense and the SAT-based SUFLA solver. A new hardware description language, DE2, is described. DE2 has a number of unique features geared towards simplifying formal verification, including a relatively simple formal semantics, support for the description of circuit generators, and support for embedding non-functional constructs within a hardware design. The composition of these techniques extend our knowledge of the languages and logics needed for formal verification and should reduce the human effort required to verify large hardware circuit models.

Functional verification is a critical problem facing the semiconductor industry: hardware designs are extremely complex and highly optimized, and even a single bug in deployed systems can cost more than $10 billion. We focus on the verification of pipelining, a key optimization that appears extensively in hardware systems such as microprocessors, multicore systems, and cache coherence protocols. Existing techniques for verifying pipelined machines either consume excessive amounts of time, effort, and resources, or are not applicable at the bit-level, the level of abstraction at which commercial systems are designed and functionally verified. We present a highly automated, efficient, compositional, and scalable refinement-based approach for the verification of bit-level pipelined machines. Our contributions include: (1) A complete compositional reasoning framework based on refinement. Our notion of refinement guarantees that pipelined machines satisfy the same safety and liveness properties as their instruction set architectures. In addition, our compositional framework can be used to decompose correctness proofs into smaller, more manageable pieces, leading to drastic reductions in verification times and a high-degree of scalability. (2) The development of ACL2-SMT, a verification system that integrates the popular ACL2 theorem prover (winner of the 2005 ACM Software System Award) with decision procedures. ACL2-SMT allows us to seamlessly take advantage of the two main approaches to hardware verification: theorem proving and decision procedures. (3) A proof methodology based on our compositional reasoning framework and ACL2-SMT that allows us to reduce the bit-level verification problem to a sequence of highly automated proof steps. (4) A collection of general-purpose refinement maps, functions that relate pipelined machine states to instruction set architecture states. These refinement maps provide more flexibility and lead to increased verification efficiency. The effectiveness of our approach is demonstrated by verifying various pipelined machine models, including a bit-level, Intel XScale inspired processor that implements 593 instructions and includes features such as branch prediction, precise exceptions, and predicated instruction execution.

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