Automated Program Verification Research Articles

Monotone Procedure Summarization via Vector Addition Systems and Inductive Potentials

This paper presents a technique for summarizing recursive procedures operating on integer variables. The motivation of our work is to create more predictable program analyzers, and in particular to formally guarantee compositionality and monotonicity of procedure summarization. To summarize a procedure, we compute its best abstraction as a vector addition system with resets (VASR) and exactly summarize the executions of this VASR over the context-free language of syntactic paths through the procedure. We improve upon this technique by refining the language of syntactic paths using (automatically synthesized) linear potential functions that bound the number of recursive calls within valid executions of the input program. We implemented our summarization technique in an automated program verification tool; our experimental evaluation demonstrates that our technique computes more precise summaries than existing abstract interpreters and that our tool’s verification capabilities are comparable with state-of-the-art software model checkers.

On algebraic array theories

Automatic verification of programs manipulating arrays relies on specialised decision procedures. A methodology to classify the theories handled by these procedures is introduced. It is based on decomposition theorems in the style of Feferman and Vaught. The method is applied to obtain an extension of combinatory array logic that is closed under propositional operations and Hoare triples. A classification according to expressiveness of six different fragments studied in the literature is given.

Distributed bounded model checking

Program verification is a resource-hungry task. This paper looks at the problem of parallelizing SMT-based automated program verification, specifically bounded model-checking, so that it can be distributed and executed on a cluster of machines. We present an algorithm that dynamically unfolds the call graph of the program and frequently splits it to create sub-tasks that can be solved in parallel. The algorithm is adaptive, controlling the splitting rate according to available resources, and also leverages information from the SMT solver to split where most complexity lies in the search. We implemented our algorithm by modifying Corral, the verifier used by Microsoft’s Static Driver Verifier (SDV), and evaluate it on a series of hard SDV benchmarks.

An Artificial Immune System Approach to Automated Program Verification: Towards a Theory of Undecidability in Biological Computing

An Artificial Immune System Approach to Automated Program Verification: Towards a Theory of Undecidability in Biological Computing

RustHorn: CHC-based Verification for Rust Programs

Reduction to satisfiability of constrained Horn clauses (CHCs) is a widely studied approach to automated program verification. Current CHC-based methods, however, do not work very well for pointer-manipulating programs, especially those with dynamic memory allocation. This article presents a novel reduction of pointer-manipulating Rust programs into CHCs, which clears away pointers and memory states by leveraging Rust’s guarantees on permission. We formalize our reduction for a simplified core of Rust and prove its soundness and completeness. We have implemented a prototype verifier for a subset of Rust and confirmed the effectiveness of our method.

Полная решающая процедура для теории ограниченной адресной арифметики

The process of developing C programs is quite often prone to errors related to the uses of pointer arithmetic and operations on memory addresses. This promotes a need in developing various tools for automated program verification. One of the techniques frequently employed by those tools is invocation of appropriate decision procedures implemented within existing SMT-solvers. But at the same time both the SMT standard and most existing SMT-solvers lack the relevant logics (combinations of logical theories) for directly and precisely modelling the semantics of pointer operations in C. One of the possible ways to support these logics is to implement them in an SMT solver, but this approach can be time-consuming (as requires modifying the solver’s source code), inflexible (introducing any changes to the theory’s signature or semantics can be unreasonably hard) and limited (every solver has to be supported separately). Another way is to design and implement custom quantifier instantiation strategies. These strategies can be then used to translate formulas in the desired theory combinations to formulas in well-supported decidable logics such as QF_UFLIA. In this paper, we present an instantiation procedure for translating formulas in the theory of bounded pointer arithmetic into the QF_UFLIA logic. We formally proved soundness and completeness of our instantiation procedure in Isabelle/HOL. The paper presents an informal description of this proof of the proposed procedure. The theory of bounded pointer arithmetic itself was formulated based on known errors regarding the correct use of pointer arithmetic operations in industrial code as well as the semantics of these operations specified in the C standard. Similar procedure can also be defined for a practically relevant fragment of the theory of bit vectors (monotone propositional combinations of equalities between bitwise expressions). Our approach is sufficient to obtain efficient decision procedures implemented as Isabelle/HOL proof methods for several decidable logical theories used in C program verification by relying on the existing capabilities of well-known SMT solvers, such as Z3 and proof reconstruction capabilities of the Isabelle/HOL proof assistant.

Deciding memory safety for single-pass heap-manipulating programs

We investigate the decidability of automatic program verification for programs that manipulate heaps, and in particular, decision procedures for proving memory safety for them. We extend recent work that identified a decidable subclass of uninterpreted programs to a class of alias-aware programs that can update maps. We apply this theory to develop verification algorithms for memory safety— determining if a heap-manipulating program that allocates and frees memory locations and manipulates heap pointers does not dereference an unallocated memory location. We show that this problem is decidable when the initial allocated heap forms a forest data-structure and when programs are streaming-coherent , which intuitively restricts programs to make a single pass over a data-structure. Our experimental evaluation on a set of library routines that manipulate forest data-structures shows that common single-pass algorithms on data-structures often fall in the decidable class, and that our decision procedure is efficient in verifying them.

Leveraging Horn clause solving for compositional verification of PLC software

Real-world PLC software is modular and composed of many different function blocks. Nevertheless, common approaches to PLC software verification do not leverage this but resort to inlining, or analyse instances of the same function block type independently. With the advent of constrained Horn clauses as the basis for automated program verification, many state-of-the-art verification procedures build upon them. We illustrate how this formalism allows for a uniform characterisation of PLC program semantics and safety goals, derived from reactive systems safety foundations. Furthermore, we give a natural extension of the resulting encoding which enables compositional reasoning about modular software. Due to the cyclic execution of PLCs, an engineer’s mental model of a single function block often exhibits state machine semantics – partitioning a block’s behaviour into different modes of operation. We illustrate how such a mode space, and similar high-level knowledge, can be integrated with our compositional characterisation. We investigate the impact of each technique on the model checking performance by characterising PLC software verification problems, both in a non-compositional and a compositional way that may incorporate mode transitions, and solving them with an SMT solver. Evaluation of our prototypical implementation on examples from the PLCopen Safety library shows the effectiveness of both the chosen formalism and using high-level summaries.

Toward automatic verification of quantum programs

Abstract This paper summarises the results obtained by the author and his collaborators in a program logic approach to the verification of quantum programs, including quantum Hoare logic, invariant generation and termination analysis for quantum programs. It also introduces the notion of proof outline and several auxiliary rules for more conveniently reasoning about quantum programs. Some problems for future research are proposed at the end of the paper.

On the decidability of the existence of polyhedral invariants in transition systems

Automated program verification often proceeds by exhibiting inductive invariants entailing the desired properties. For numerical properties, a classical class of invariants is convex polyhedra: solution sets of system of linear (in)equalities. Forty years of research on convex polyhedral invariants have focused, on the one hand, on identifying “easier” subclasses, on the other hand on heuristics for finding general convex polyhedra. These heuristics are however not guaranteed to find polyhedral inductive invariants when they exist. To our best knowledge, the existence of polyhedral inductive invariants has never been proved to be undecidable. In this article, we show that the existence of convex polyhedral invariants is undecidable, even if there is only one control state in addition to the ``bad'' one. The question is still open if one is not allowed any nonlinear constraint.

Intuitive robot programming through environment perception, augmented reality simulation and automated program verification

The increasing complexity of products and machines as well as short production cycles with small lot sizes present great challenges to production industry. Both, the programming of industrial robots in online mode using hand-held control devices or in offline mode using text-based programming requires specific knowledge of robotics and manufacturer-dependent robot control systems. In particular for small and medium-sized enterprises the machine control software needs to be easy, intuitive and usable without time-consuming learning steps, even for employees with no in-depth knowledge of information technology. To simplify the programming of application programs for industrial robots, we extended a cloud-based, task-oriented robot control system with environment perception and plausibility check functions. For the environment perception a depth camera and pointcloud processing hardware were installed. We detect objects located in the robot’s workspace by pointcloud processing with ROS and the PCL and add them to the augmented reality user interface of the robot control. The combination of process knowledge from task-oriented application programming and information about available workpieces from automated image processing enables a plausibility check and verification of the robot program before execution. After a robot program has been approved by the plausibility check, it is tested in an augmented reality simulation for collisions with the detected objects before deployment to the physical robot hardware. Experiments were carried out to evaluate the effectiveness of the developed extensions and confirmed their functionality.

Control Explicit--Data Symbolic Model Checking

Automatic verification of programs and computer systems with data nondeterminism (e.g., reading from user input) represents a significant and well-motivated challenge. The case of parallel programs is especially difficult, because then also the control flow nontrivially complicates the verification process. We apply the techniques of explicit-state model checking to account for the control aspects of a program to be verified and use set-based reduction of the data flow, thus handling the two sources of nondeterminism separately. We build the theory of set-based reduction using first-order formulae in the bit-vector theory to encode the sets of variable evaluations representing program data. These representations are tested for emptiness and equality (state matching) during the verification, and we harness modern satisfiability modulo theory solvers to implement these tests. We design two methods of implementing the state matching, one using quantifiers and one that is quantifier-free, and we provide both analytical and experimental comparisons. Further experiments evaluate the efficiency of the set-based reduction method, showing the classical, explicit approach to fail to scale with the size of data domains. Finally, we propose and evaluate two heuristics to decrease the number of expensive satisfiability queries, together yielding a 10-fold speedup.

Finite Countermodel Based Verification for Program Transformation (A Case Study)

Both automatic program verification and program transformation are based on program analysis. In the past decade a number of approaches using various automatic general-purpose program transformation techniques (partial deduction, specialization, supercompilation) for verification of unreachability properties of computing systems were introduced and demonstrated. On the other hand, the semantics based unfold-fold program transformation methods pose themselves diverse kinds of reachability tasks and try to solve them, aiming at improving the semantics tree of the program being transformed. That means some general-purpose verification methods may be used for strengthening program transformation techniques. This paper considers the question how finite countermodels for safety verification method might be used in Turchin's supercompilation method. We extract a number of supercompilation sub-algorithms trying to solve reachability problems and demonstrate use of an external countermodel finder for solving some of the problems.

A Symbolic Model for Timed Concurrent Constraint Programming

Concurrent Constraint Programming (ccp) is a model for concurrency where agents interact with each other by telling and asking constraints (i.e., formulas in logic) into a shared store of partial information. The ntcc calculus extends ccp with the notion of discrete time-units for the specification of reactive systems. Moreover, ntcc features constructors for non-deterministic choices and asynchronous behavior, thus allowing for (1) synchronization of processes via constraint entailment during a time-unit and (2) synchronization of processes along time-intervals. In this paper we develop the techniques needed for the automatic verification of ntcc programs based on symbolic model checking. We show that the internal transition relation, modeling the behavior of processes during a time-unit (1 above), can be symbolically represented by formulas in a suitable fragment of linear time temporal logic. Moreover, by using standard techniques as difference decision diagrams, we provide a compact representation of these constraints. Then, relying on a fixpoint characterization of the timed constructs, we obtain a symbolic model of the observable transition (2 above). We prove that our construction is correct with respect to the operational semantics. Finally, we introduce a prototypical tool implementing our method.

Accelerating temporal verification of Simulink diagrams using satisfiability modulo theories

Automatic verification of programs and computer systems with input variables represents a significant and well-motivated challenge. The case of Simulink diagrams is especially difficult, because there the inputs are read iteratively, and the number of input variables is in theory unbounded. We apply the techniques of explicit model checking to account for the temporal (control) aspects of verification and use set-based representation of data, thus handling both sources of non-determinism present in the verification. Two different representations of sets are evaluated in scalability with respect to the range of input variables. Explicit (enumerating) sets are very fast for small ranges but fail to scale. Symbolic sets, represented as first-order formulas in the bit-vector theory and compared using satisfiability modulo theory solvers, scale well to arbitrary (though still bounded) range of input variables. To leverage the combined strengths of explicit and symbolic representations, we have designed a hybrid representation which we showed to outperform both pure representations. Thus, the proposed method allows complete automatic verification without the need to limit the non-determinism of input. Moreover, the principle underlying the hybrid representation entails inferring knowledge about the system under verification, which the developers did not explicitly include in the system, and which can significantly accelerate the verification process.

An innovative approach for automatic generation, verification and optimization of part programs in turning

Continuous innovation of products and optimization of manufacturing processes are of fundamental importance for preserving competitiveness. In the last decades, several approaches based on analytic models for optimization of basic machining operations such as cylindrical turning and face milling have been developed. However, the analytic approaches may not be adequate for real industrial applications, since they are based on average cutting parameters and thus they are not capable of taking into account the effect of complex geometries and instantaneous cutting conditions. In this paper, an innovative integrated system for automatic generation of optimized part programs in turning based on realistic machining simulation is proposed. The system components are described in detail and the machining simulator is validated by comparison with the results of real cutting tests. Then, the optimization approach is applied to a simple case study. The results show that the behavior of the cost function is rather complex, even for simple workpieces. Moreover, the simulator can detect unfeasible combinations of cutting parameters and thus reduce inline part program refinement and optimization. The optimal combination of cutting parameters determined by the new system was competitive with the solutions derived from tool specifications or proposed by a machining expert.

Modular reasoning about heap paths via effectively propositional formulas

First order logic with transitive closure, and separation logic enable elegant interactive verification of heap-manipulating programs. However, undecidabilty results and high asymptotic complexity of checking validity preclude complete automatic verification of such programs, even when loop invariants and procedure contracts are specified as formulas in these logics. This paper tackles the problem of procedure-modular verification of reachability properties of heap-manipulating programs using efficient decision procedures that are complete: that is, a SAT solver must generate a counterexample whenever a program does not satisfy its specification. By (a) requiring each procedure modifies a fixed set of heap partitions and creates a bounded amount of heap sharing, and (b) restricting program contracts and loop invariants to use only deterministic paths in the heap, we show that heap reachability updates can be described in a simple manner. The restrictions force program specifications and verification conditions to lie within a fragment of first-order logic with transitive closure that is reducible to effectively propositional logic, and hence facilitate sound, complete and efficient verification. We implemented a tool atop Z3 and report on preliminary experiments that establish the correctness of several programs that manipulate linked data structures.

A type-directed abstraction refinement approach to higher-order model checking

The trivial-automaton model checking problem for higher-order recursion schemes has become a widely studied object in connection with the automatic verification of higher-order programs. The problem is formidably hard: despite considerable progress in recent years, no decision procedures have been demonstrated to scale robustly beyond recursion schemes that comprise more than a few hundred rewrite rules. We present a new, fixed-parameter polynomial time algorithm, based on a novel, type directed form of abstraction refinement in which behaviours of a scheme are distinguished by the abstraction according to the intersection types that they inhabit (the properties that they satisfy). Unlike other intersection type approaches, our algorithm reasons both about acceptance by the property automaton and acceptance by its dual, simultaneously, in order to minimize the amount of work done by converging on the solution to a problem instance from both sides. We have constructed Preface, a prototype implementation of the algorithm, and assembled an extensive body of evidence to demonstrate empirically that the algorithm readily scales to recursion schemes of several thousand rules, well beyond the capabilities of current state-of-the-art higher-order model checkers.

Automatic versus interactive program verification

We report on experiences in using two very different program verification technologies. One of them is based on object-oriented assertion languages and it comes with automatic static verification of object-oriented programs. The other technology is independent of a programming language or programming paradigm and it offers static interactive verification of very complex constraints. These two technologies were applied to the problem of static verification of object-oriented transactions. The problem was chosen because database technologies are not equipped to handle general integrity constraints and verification technologies are not used to verify transactions. The implications of static verification on data integrity, effciency, and reliability of transactions are significant.

A Shape Graph Logic and A Shape System

Analysis and verification of pointer programs are still difficult problems so far. This paper uses a shape graph logic and a shape system to solve these problems in two stages. First, shape graphs at every program point are constructed using an analysis tool. Then, they are used to support the verification of other properties (e.g., orderedness). Our prototype supports automatic verification of programs manipulating complex data structures such as splay trees, treaps, AVL trees and AA trees, etc. The proposed shape graph logic, as an extension to Hoare logic, uses shape graphs directly as assertions. It can be used in the analysis and verification of programs manipulating mutable data structures. The benefit using shape graphs as assertions is that it is convenient for acquiring the relations between pointers in the verification stage. The proposed shape system requires programmers to provide lightweight shape declarations in recursive structure type declarations. It can help rule out programs that construct shapes deviating from what programmers expect (reflected in shape declarations) in the analysis stage. As a benefit, programmers need not provide specifications (e.g., pre-/post-conditions, loop invariants) about pointers. Moreover, we present a method doing verification in the second stage using traditional Hoare logic rules directly by eliminating aliasing with the aid of shape graphs. Thus, verification conditions could be discharged by general theorem provers.