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A Framework for Verifying Bit-Level Pipelined Machines Based on Automated Deduction and Decision Procedures

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Abstract

We describe an approach to verifying bit-level pipelined machine models using a combination of deductive reasoning and decision procedures. While theorem-proving systems such as ACL2 have been used to verify bit-level designs, they typically require extensive expert user support. Decision procedures such as those implemented in UCLID can be used to automatically and efficiently verify term-level pipelined machine models, but these models use numerous abstractions, implement a subset of the instruction set, and are far from executable. We show that by integrating UCLID with the ACL2 theorem-proving system, we can use ACL2 to reduce the proof that an executable, bit-level machine refines its instruction set architecture to a proof that a term-level abstraction of the bit-level machine refines the instruction set architecture, which is then handled automatically by UCLID. We demonstrate the efficiency of our approach by applying it to verify a complex, seven-stage, bit-level interface pipelined machine model that implements 593 instructions and has features such as branch prediction, exceptions, and predicated instruction execution. Such a proof is not possible using UCLID and would require prohibitively more effort using just ACL2.

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Authors and Affiliations

  1. College of Computing, Georgia Institute of Technology, Atlanta, Georgia, 30318, USA

    Panagiotis Manolios

  2. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, 30318, USA

    Sudarshan K. Srinivasan

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  1. Panagiotis Manolios
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  2. Sudarshan K. Srinivasan
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Correspondence to Panagiotis Manolios.

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This research was funded in part by NSF grants CCF-0429924, IIS-0417413, and CCF-0438871.

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Manolios, P., Srinivasan, S.K. A Framework for Verifying Bit-Level Pipelined Machines Based on Automated Deduction and Decision Procedures. J Autom Reasoning 37, 93–116 (2006). https://doi.org/10.1007/s10817-006-9035-0

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