This dissertation shows that the bounded property verification of hardware Register Transfer Level (RTL) designs can be efficiently performed by precise abstract interpretation of a software representation of the RTL. The first part of this dissertation presents a novel framework for RTL verification using native software analyzers. To this end, we first present a translation of the hardware circuit expressed in Verilog RTL into the software in C called the software netlist. We then present the application of native software analyzers based on SAT/SMT-based decision procedures as well as abstraction-based techniques such as abstract interpretation for the formal verification of the software netlist design generated from the hardware RTL. In particular, we show that the path-based symbolic execution techniques, commonly used for automatic test case generation in system softwares, are also effective for proving bounded safety as well as detecting bugs in the software netlist designs. Furthermore, by means of experiments, we show that abstract interpretation techniques, commonly used for static program analysis, can also be used for bounded as well as unbounded safety property verification of the software netlist designs. However, the analysis using abstract interpretation shows high degree of imprecision on our benchmarks which is handled by manually guiding the analysis with various trace partitioning directives. The second part of this dissertation presents a new theoretical framework and a practical instantiation for automatically refining the precision of abstract interpretation using Conflict Driven Clause Learning (CDCL)-style analysis. The theoretical contribution is the abstract interpretation framework that generalizes CDCL to precise safety verification for automatic transformer refinement called Abstract Conflict Driven Learning for Safety (ACDLS). The practical contribution instantiates ACDLS over a template polyhedra abstract domain for bounded safety verification of the software netlist designs. We experimentally show that ACDLS is more efficient than a SAT-based analysis as well as sufficiently more precise than a commercial abstract interpreter.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:748966 |
| Date | January 2018 |
| Creators | Mukherjee, Rajdeep |
| Contributors | Melham, Tom ; Kroening, Daniel |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:680f0093-0405-4a0b-88dc-c4d7177d840f |
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