Formal Analysis of Arithmetic Circuits using Computer Algebra - Verification, Abstraction and Reverse Engineering

Despite a considerable progress in verification and abstraction of random and control logic, advances in formal verification of arithmetic designs have been lagging. This can be attributed mostly to the difficulty in an efficient modeling of arithmetic circuits and datapaths without resorting to computationally expensive Boolean methods, such as Binary Decision Diagrams (BDDs) and Boolean Satisfiability (SAT), that require “bit blasting”, i.e., flattening the design to a bit-level netlist. Approaches that rely on computer algebra and Satisfiability Modulo Theories (SMT) methods are either too abstract to handle the bit-level nature of arithmetic designs or require solving computationally expensive decision or satisfiability problems. The work proposed in this thesis aims at overcoming the limitations of analyzing arithmetic circuits, specifically at the post-synthesized phase. It addresses the verification, abstraction and reverse engineering problems of arithmetic circuits at an algebraic level, treating an arithmetic circuit and its specification as a properly constructed algebraic system. The proposed technique solves these problems by function extraction, i.e., by deriving arithmetic function computed by the circuit from its low-level circuit implementation using computer algebraic rewriting technique. The proposed techniques work on large integer arithmetic circuits and finite field arithmetic circuits, up to 512-bit wide containing millions of logic gates

Doctor of Philosophy

dissertationWith the spread of internet and mobile devices, transferring information safely and securely has become more important than ever. Finite fields have widespread applications in such domains, such as in cryptography, error correction codes, among many others. In most finite field applications, the field size - and therefore the bit-width of the operands - can be very large. The high complexity of arithmetic operations over such large fields requires circuits to be (semi-) custom designed. This raises the potential for errors/bugs in the implementation, which can be maliciously exploited and can compromise the security of such systems. Formal verification of finite field arithmetic circuits has therefore become an imperative. This dissertation targets the problem of formal verification of hardware implementations of combinational arithmetic circuits over finite fields of the type F2k . Two specific problems are addressed: i) verifying the correctness of a custom-designed arithmetic circuit implementation against a given word-level polynomial specification over F2k ; and ii) gate-level equivalence checking of two different arithmetic circuit implementations. This dissertation proposes polynomial abstractions over finite fields to model and represent the circuit constraints. Subsequently, decision procedures based on modern computer algebra techniques - notably, Gr¨obner bases-related theory and technology - are engineered to solve the verification problem efficiently. The arithmetic circuit is modeled as a polynomial system in the ring F2k [x1, x2, · · · , xd], and computer algebrabased results (Hilbert's Nullstellensatz) over finite fields are exploited for verification. Using our approach, experiments are performed on a variety of custom-designed finite field arithmetic benchmark circuits. The results are also compared against contemporary methods, based on SAT and SMT solvers, BDDs, and AIG-based methods. Our tools can verify the correctness of, and detect bugs in, up to 163-bit circuits in F2163 , whereas contemporary approaches are infeasible beyond 48-bit circuits

Tools and Algorithms for the Construction and Analysis of Systems

This open access two-volume set constitutes the proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021, which was held during March 27 – April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The total of 41 full papers presented in the proceedings was carefully reviewed and selected from 141 submissions. The volume also contains 7 tool papers; 6 Tool Demo papers, 9 SV-Comp Competition Papers. The papers are organized in topical sections as follows: Part I: Game Theory; SMT Verification; Probabilities; Timed Systems; Neural Networks; Analysis of Network Communication. Part II: Verification Techniques (not SMT); Case Studies; Proof Generation/Validation; Tool Papers; Tool Demo Papers; SV-Comp Tool Competition Papers

Effective SAT solving

A growing number of problem domains are successfully being tackled by SAT solvers. This thesis contributes to that trend by pushing the state-of-the-art of core SAT algorithms and their implementation, but also in several important application areas. It consists of five papers: the first details the implementation of the SAT solver MiniSat and the other four papers discuss specific issues related to different application domains. In the first paper, catering to the trend of extending and adapting SAT solvers, we present a detailed description of MiniSat, a SAT solver designed for that particular purpose. The description additionally bridges a gap between theory and practice, serving as a tutorial on modern SAT solving algorithms. Among other things, we describe how to solve a series of related SAT problems efficiently, called incremental SAT solving. For finding finite first order models the MACE-style method that is based on SAT solving is well-known. In the second paper we improve the basic method with several techniques that can be loosely classified as either transformations that make the reduction to SAT result in fewer clauses or techniques that are designed to speed up the search of the SAT solver. The resulting tool, called Paradox, won the SAT/Models division of the CASC competition in 2003 and has not been beaten since by a single general purpose model finding tool. In the last decade the interest in methods for safety property verification that are based on SAT solving has been steadily growing. One example of such a method is temporal induction. The method requires a sequence of increasingly stronger induction proofs to be performed. In the third paper we show how this sequence of proofs can be solved efficiently using incremental SAT solving. The last two papers consider two frequently occurring types of encodings: (1) the problem of encoding circuits into CNF, and (2) encoding 0-1 integer linear programming into CNF and how to use incremental SAT to solve the intended ptimization problem. There are several encoding patterns that occur over and over again in this thesis but also elsewhere. The most noteworthy are: incremental SAT, lazy encoding of constraints, and bit-wise encoding of arithmetic influenced by hardware designs for adders and multipliers. The general conclusion is: deploying SAT solvers effectively requires implementations that are efficient, yet easily adaptable to specific application needs. Moreover, to get the best results, it is worth spending effort to make sure that one uses the best codings possible for an application. However, it is important to note that this is not absolutely necessary. For some applications naive problem codings work just fine which is indeed part of the appeal of using SAT solving

Doctor of Philosophy

dissertationAbstraction plays an important role in digital design, analysis, and verification, as it allows for the refinement of functions through different levels of conceptualization. This dissertation introduces a new method to compute a symbolic, canonical, word-level abstraction of the function implemented by a combinational logic circuit. This abstraction provides a representation of the function as a polynomial Z = F(A) over the Galois field F2k , expressed over the k-bit input to the circuit, A. This representation is easily utilized for formal verification (equivalence checking) of combinational circuits. The approach to abstraction is based upon concepts from commutative algebra and algebraic geometry, notably the Grobner basis theory. It is shown that the polynomial F(A) can be derived by computing a Grobner basis of the polynomials corresponding to the circuit, using a specific elimination term order based on the circuits topology. However, computing Grobner bases using elimination term orders is infeasible for large circuits. To overcome these limitations, this work introduces an efficient symbolic computation to derive the word-level polynomial. The presented algorithms exploit i) the structure of the circuit, ii) the properties of Grobner bases, iii) characteristics of Galois fields F2k , and iv) modern algorithms from symbolic computation. A custom abstraction tool is designed to efficiently implement the abstraction procedure. While the concept is applicable to any arbitrary combinational logic circuit, it is particularly powerful in verification and equivalence checking of hierarchical, custom designed and structurally dissimilar Galois field arithmetic circuits. In most applications, the field size and the datapath size k in the circuits is very large, up to 1024 bits. The proposed abstraction procedure can exploit the hierarchy of the given Galois field arithmetic circuits. Our experiments show that, using this approach, our tool can abstract and verify Galois field arithmetic circuits up to 1024 bits in size. Contemporary techniques fail to verify these types of circuits beyond 163 bits and cannot abstract a canonical representation beyond 32 bits

Doctor of Philosophy

dissertationFormal verification of hardware designs has become an essential component of the overall system design flow. The designs are generally modeled as finite state machines, on which property and equivalence checking problems are solved for verification. Reachability analysis forms the core of these techniques. However, increasing size and complexity of the circuits causes the state explosion problem. Abstraction is the key to tackling the scalability challenges. This dissertation presents new techniques for word-level abstraction with applications in sequential design verification. By bundling together k bit-level state-variables into one word-level constraint expression, the state-space is construed as solutions (variety) to a set of polynomial constraints (ideal), modeled over the finite (Galois) field of 2^k elements. Subsequently, techniques from algebraic geometry -- notably, Groebner basis theory and technology -- are researched to perform reachability analysis and verification of sequential circuits. This approach adds a "word-level dimension" to state-space abstraction and verification to make the process more efficient. While algebraic geometry provides powerful abstraction and reasoning capabilities, the algorithms exhibit high computational complexity. In the dissertation, we show that by analyzing the constraints, it is possible to obtain more insights about the polynomial ideals, which can be exploited to overcome the complexity. Using our algorithm design and implementations, we demonstrate how to perform reachability analysis of finite-state machines purely at the word level. Using this concept, we perform scalable verification of sequential arithmetic circuits. As contemporary approaches make use of resolution proofs and unsatisfiable cores for state-space abstraction, we introduce the algebraic geometry analog of unsatisfiable cores, and present algorithms to extract and refine unsatisfiable cores of polynomial ideals. Experiments are performed to demonstrate the efficacy of our approaches