Results 1 - 10
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42
Program analysis as constraint solving
- In PLDI
, 2008
"... A constraint-based approach to invariant generation in programs translates a program into constraints that are solved using off-theshelf constraint solvers to yield desired program invariants. In this paper we show how the constraint-based approach can be used to model a wide spectrum of program ana ..."
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Cited by 54 (11 self)
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A constraint-based approach to invariant generation in programs translates a program into constraints that are solved using off-theshelf constraint solvers to yield desired program invariants. In this paper we show how the constraint-based approach can be used to model a wide spectrum of program analyses in an expressive domain containing disjunctions and conjunctions of linear inequalities. In particular, we show how to model the problem of context-sensitive interprocedural program verification. We also present the first constraint-based approach to weakest precondition and strongest postcondition inference. The constraints we generate are boolean combinations of quadratic inequalities over integer variables. We reduce these constraints to SAT formulae using bitvector modeling and use off-the-shelf SAT solvers to solve them. Furthermore, we present interesting applications of the above analyses, namely bounds analysis and generation of most-general counter-examples for both safety and termination properties. We also present encouraging preliminary experimental results demonstrating the feasibility of our technique on a variety of challenging examples.
Path invariants
- In PLDI
, 2007
"... The success of software verification depends on the ability to find a suitable abstraction of a program automatically. We propose a method for automated abstraction refinement which overcomes some limitations of current predicate discovery schemes. In current schemes, the cause of a false alarm is i ..."
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Cited by 50 (6 self)
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The success of software verification depends on the ability to find a suitable abstraction of a program automatically. We propose a method for automated abstraction refinement which overcomes some limitations of current predicate discovery schemes. In current schemes, the cause of a false alarm is identified as an infeasible error path, and the abstraction is refined in order to remove that path. By contrast, we view the cause of a false alarm —the spurious counterexample — as a full-fledged program, namely, a fragment of the original program whose control-flow graph may contain loops and represent unbounded computations. There are two advantages to using such path programs as counterexamples for abstraction refinement. First, we can bring the whole machinery of program analysis to bear on path programs, which are typically small compared to the original program. Specifically, we use constraint-based invariant generation to automatically infer invariants of path programs —so-called path invariants. Second, we use path invariants for abstraction refinement in order to remove not one infeasibility at a time, but at once all (possibly infinitely many) infeasible error computations that are represented by a path program. Unlike previous predicate discovery schemes, our method handles loops without unrolling them; it infers abstractions that involve universal quantification and naturally incorporates disjunctive reasoning.
Proving non-termination
- In POPL
, 2008
"... The search for proof and the search for counterexamples (bugs) are complementary activities that need to be pursued concurrently in order to maximize the practical success rate of verification tools. While this is well-understood in safety verification, the current focus of liveness verification has ..."
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Cited by 46 (7 self)
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The search for proof and the search for counterexamples (bugs) are complementary activities that need to be pursued concurrently in order to maximize the practical success rate of verification tools. While this is well-understood in safety verification, the current focus of liveness verification has been almost exclusively on the search for termination proofs. A counterexample to termination is an infinite program execution. In this paper, we propose a method to search for such counterexamples. The search proceeds in two phases. We first dynamically enumerate lasso-shaped candidate paths for counterexamples, and then statically prove their feasibil-ity. We illustrate the utility of our nontermination prover, called TNT, on several nontrivial examples, some of which require bit-level reasoning about integer representations.
Modular Data Structure Verification
- EECS DEPARTMENT, MASSACHUSETTS INSTITUTE OF TECHNOLOGY
, 2007
"... This dissertation describes an approach for automatically verifying data structures, focusing on techniques for automatically proving formulas that arise in such verification. I have implemented this approach with my colleagues in a verification system called Jahob. Jahob verifies properties of Java ..."
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Cited by 43 (20 self)
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This dissertation describes an approach for automatically verifying data structures, focusing on techniques for automatically proving formulas that arise in such verification. I have implemented this approach with my colleagues in a verification system called Jahob. Jahob verifies properties of Java programs with dynamically allocated data structures. Developers write Jahob specifications in classical higher-order logic (HOL); Jahob reduces the verification problem to deciding the validity of HOL formulas. I present a new method for proving HOL formulas by combining automated reasoning techniques. My method consists of 1) splitting formulas into individual HOL conjuncts, 2) soundly approximating each HOL conjunct with a formula in a more tractable fragment and 3) proving the resulting approximation using a decision procedure or a theorem prover. I present three concrete logics; for each logic I show how to use it to approximate HOL formulas, and how to decide the validity of formulas in this logic. First, I present an approximation of HOL based on a translation to first-order logic, which enables the use of existing resolution-based theorem provers. Second, I present an approximation of HOL based on field constraint analysis, a new technique that enables
Invariant synthesis for combined theories
- In Proc. VMCAI, LNCS 4349
, 2007
"... Abstract. We present a constraint-based algorithm for the synthesis of invariants expressed in the combined theory of linear arithmetic and uninterpreted function symbols. Given a set of programmer-specified invariant templates, our algorithm reduces the invariant synthesis problem to a sequence of ..."
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Cited by 42 (8 self)
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Abstract. We present a constraint-based algorithm for the synthesis of invariants expressed in the combined theory of linear arithmetic and uninterpreted function symbols. Given a set of programmer-specified invariant templates, our algorithm reduces the invariant synthesis problem to a sequence of arithmetic constraint satisfaction queries. Since the combination of linear arithmetic and uninterpreted functions is a widely applied predicate domain for program verification, our algorithm provides a powerful tool to statically and automatically reason about program correctness. The algorithm can also be used for the synthesis of invariants over arrays and set data structures, because satisfiability questions for the theories of sets and arrays can be reduced to the theory of linear arithmetic with uninterpreted functions. We have implemented our algorithm and used it to find invariants for a low-level memory allocator writteninC. 1
Constraint-Based Approach for Analysis of Hybrid Systems
- of Lecture Notes in Computer Science
, 2008
"... Abstract. This paper presents a constraint-based technique for discovering a rich class of inductive invariants (disjunctions of polynomial inequalities of bounded degree) for verification of hybrid systems. The key idea is to introduce a template for the unknown invariants and then translate the ve ..."
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Cited by 41 (10 self)
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Abstract. This paper presents a constraint-based technique for discovering a rich class of inductive invariants (disjunctions of polynomial inequalities of bounded degree) for verification of hybrid systems. The key idea is to introduce a template for the unknown invariants and then translate the verification condition of the hybrid system into an ∃ ∀ constraint over the template unknowns (which are variables over reals) by making use of the fact that vector fields must point inwards at the boundary. These constraints are then solved using Farkas lemma. We also present preliminary experimental results that demonstrate the feasibility of our approach of solving the ∃ ∀ constraints generated from models of realworld hybrid systems. 1
Program Verification using Templates over Predicate Abstraction
"... We address the problem of automatically generating invariants with quantified and boolean structure for proving the validity of given assertions or generating pre-conditions under which the assertions are valid. We present three novel algorithms, having different strengths, that combine template and ..."
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Cited by 37 (3 self)
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We address the problem of automatically generating invariants with quantified and boolean structure for proving the validity of given assertions or generating pre-conditions under which the assertions are valid. We present three novel algorithms, having different strengths, that combine template and predicate abstraction based formalisms to discover required sophisticated program invariants using SMT solvers. Two of these algorithms use an iterative approach to compute fixed-points (one computes a least fixed-point and the other computes a greatest fixed-point), while the third algorithm uses a constraint based approach to encode the fixed-point. The key idea in all these algorithms is to reduce the problem of invariant discovery to that of finding optimal solutions for unknowns (over conjunctions of some predicates from a given set) in a template formula such that
Deciding Boolean Algebra with Presburger Arithmetic
- J. of Automated Reasoning
"... Abstract. We describe an algorithm for deciding the first-order multisorted theory BAPA, which combines 1) Boolean algebras of sets of uninterpreted elements (BA) and 2) Presburger arithmetic operations (PA). BAPA can express the relationship between integer variables and cardinalities of unbounded ..."
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Cited by 33 (26 self)
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Abstract. We describe an algorithm for deciding the first-order multisorted theory BAPA, which combines 1) Boolean algebras of sets of uninterpreted elements (BA) and 2) Presburger arithmetic operations (PA). BAPA can express the relationship between integer variables and cardinalities of unbounded finite sets, and supports arbitrary quantification over sets and integers. Our original motivation for BAPA is deciding verification conditions that arise in the static analysis of data structure consistency properties. Data structures often use an integer variable to keep track of the number of elements they store; an invariant of such a data structure is that the value of the integer variable is equal to the number of elements stored in the data structure. When the data structure content is represented by a set, the resulting constraints can be captured in BAPA. BAPA formulas with quantifier alternations arise when verifying programs with annotations containing quantifiers, or when proving simulation relation conditions for refinement and equivalence of program fragments. Furthermore, BAPA constraints can be used for proving the termination of programs that manipulate data structures, as well as
An algorithm for deciding BAPA: Boolean Algebra with Presburger Arithmetic
- In 20th International Conference on Automated Deduction, CADE-20
, 2005
"... Abstract. We describe an algorithm for deciding the first-order multisorted theory BAPA, which combines 1) Boolean algebras of sets of uninterpreted elements (BA) and 2) Presburger arithmetic operations (PA). BAPA can express the relationship between integer variables and cardinalities of a priory u ..."
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Cited by 29 (12 self)
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Abstract. We describe an algorithm for deciding the first-order multisorted theory BAPA, which combines 1) Boolean algebras of sets of uninterpreted elements (BA) and 2) Presburger arithmetic operations (PA). BAPA can express the relationship between integer variables and cardinalities of a priory unbounded finite sets, and supports arbitrary quantification over sets and integers. Our motivation for BAPA is deciding verification conditions that arise in the static analysis of data structure consistency properties. Data structures often use an integer variable to keep track of the number of elements they store; an invariant of such a data structure is that the value of the integer variable is equal to the number of elements stored in the data structure. When the data structure content is represented by a set, the resulting constraints can be captured in BAPA. BAPA formulas with quantifier alternations arise when verifying programs with annotations containing quantifiers, or when proving simulation relation conditions for refinement and equivalence of program fragments. Furthermore, BAPA constraints can be used for proving the termination of programs that manipulate data structures, and have applications in constraint databases. We give a formal description of a decision procedure for BAPA, which implies the decidability of BAPA. We analyze our algorithm and obtain an elementary upper bound on the running time, thereby giving the first complexity bound for BAPA. Because it works by a reduction to PA, our algorithm yields the decidability of a combination of sets of uninterpreted elements with any decidable extension of PA. Our algorithm can also be used to yield an optimal decision procedure for BA through a reduction to PA with bounded quantifiers. We have implemented our algorithm and used it to discharge verification conditions in the Jahob system for data structure consistency checking of Java programs; our experience with the algorithm is promising. 1
Automatic modular abstractions for linear constraints, in: Principles of programming languages
- ACM
"... We propose a method for automatically generating abstract transformers for static analysis by abstract interpretation. The method focuses on linear constraints on programs operating on rational, real or floating-point variables and containing linear assignments and tests. In addition to loop-free co ..."
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Cited by 27 (6 self)
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We propose a method for automatically generating abstract transformers for static analysis by abstract interpretation. The method focuses on linear constraints on programs operating on rational, real or floating-point variables and containing linear assignments and tests. In addition to loop-free code, the same method also applies for obtaining least fixed points as functions of the precondition, which permits the analysis of loops and recursive functions. Our algorithms are based on new quantifier elimination and symbolic manipulation techniques. Given the specification of an abstract domain, and a program block, our method automatically outputs an implementation of the corresponding abstract transformer. It is thus a form of program transformation. The motivation of our work is data-flow synchronous programming languages, used for building control-command embedded systems, but it also applies to imperative and functional programming. 1
