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86
The Octagon Abstract Domain
"... ... domain for static analysis by abstract interpretation. It extends a former numerical abstract domain based on DifferenceBound Matrices and allows us to represent invariants of the form (±x ± y ≤ c), where x and y are program variables and c is a real constant. We focus on giving an efficient re ..."
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Cited by 329 (24 self)
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... domain for static analysis by abstract interpretation. It extends a former numerical abstract domain based on DifferenceBound Matrices and allows us to represent invariants of the form (±x ± y ≤ c), where x and y are program variables and c is a real constant. We focus on giving an efficient representation based on DifferenceBound Matrices—O(n²) memory cost, where n is the number of variables—and graphbased algorithms for all common abstract operators—O(n³) time cost. This includes a normal form algorithm to test equivalence of representation and a widening operator to compute least fixpoint approximations.
The ASTRÉE analyzer
 Programming Languages and Systems, Proceedings of the 14th European Symposium on Programming, volume 3444 of Lecture Notes in Computer Science
, 2005
"... Abstract. ASTRÉE is an abstract interpretationbased static program analyzer aiming at proving automatically the absence of run time errors in programs written in the C programming language. It has been applied with success to large embedded controlcommand safety critical realtime software generate ..."
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Cited by 95 (14 self)
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Abstract. ASTRÉE is an abstract interpretationbased static program analyzer aiming at proving automatically the absence of run time errors in programs written in the C programming language. It has been applied with success to large embedded controlcommand safety critical realtime software generated automatically from synchronous specifications, producing a correctness proof for complex software without any false alarm in a few hours of computation. 1
WYSINWYX: What You See Is Not What You eXecute
, 2009
"... Over the last seven years, we have developed staticanalysis methods to recover a good approximation to the variables and dynamicallyallocated memory objects of a stripped executable, and to track the flow of values through them. The paper presents the algorithms that we developed, explains how the ..."
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Cited by 89 (12 self)
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Over the last seven years, we have developed staticanalysis methods to recover a good approximation to the variables and dynamicallyallocated memory objects of a stripped executable, and to track the flow of values through them. The paper presents the algorithms that we developed, explains how they are used to recover intermediate representations (IRs) from executables that are similar to the IRs that would be available if one started from source code, and describes their application in the context of program understanding and automated bug hunting. Unlike algorithms for analyzing executables that existed prior to our work, the ones presented in this paper provide useful information about memory accesses, even in the absence of debugging information. The ideas described in the paper are incorporated in a tool for analyzing Intel x86 executables, called CodeSurfer/x86. CodeSurfer/x86 builds a system dependence graph for the program, and provides a GUI for exploring the graph by (i) navigating its edges, and (ii) invoking operations, such as forward slicing, backward slicing, and chopping, to discover how parts of the program can impact other parts. To assess the usefulness of the IRs recovered by CodeSurfer/x86 in the context of automated bug hunting, we built a tool on top of CodeSurfer/x86, called DeviceDriver Analyzer for x86
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 52 (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 fullfledged program, namely, a fragment of the original program whose controlflow 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 constraintbased invariant generation to automatically infer invariants of path programs —socalled 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.
Variance analyses from invariance analyses
 In POPL
, 2007
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 46 (13 self)
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Static analysis in disjunctive numerical domains
 In SAS ’06: Proceedings of the 13th International Symposium on Static Analysis
, 2006
"... Abstract. The convexity of numerical domains such as polyhedra, octagons, intervals and linear equalities enables tractable analysis of software for buffer overflows, null pointer dereferences and floating point errors. However, convexity also causes the analysis to fail in many common cases. Powers ..."
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Cited by 42 (5 self)
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Abstract. The convexity of numerical domains such as polyhedra, octagons, intervals and linear equalities enables tractable analysis of software for buffer overflows, null pointer dereferences and floating point errors. However, convexity also causes the analysis to fail in many common cases. Powerset extensions can remedy this shortcoming by considering disjunctions of predicates. Unfortunately, analysis using powerset domains can be exponentially more expensive as compared to analysis on the base domain. In this paper, we prove structural properties of fixed points computed in commonly used powerset extensions. We show that a fixed point computed on a powerset extension is also a fixed point in the base domain computed on an “elaboration ” of the program’s CFG structure. Using this insight, we build analysis algorithms that approach path sensitive static analysis algorithms by performing the fixed point computation on the base domain while discovering an “elaboration ” on the fly. Using restrictions on the nature of the elaborations, we design algorithms that scale polynomially in terms of the number of disjuncts. We have implemented a lightweight static analyzer as a part of the FSoft project with encouraging initial results. 1
Shape analysis with structural invariant checkers
, 2007
"... Abstract. Developersupplied data structure specifications are important to shape analyses, as they tell the analysis what information should be tracked in order to obtain the desired shape invariants. We observe that data structure checking code (e.g., used in testing or dynamic analysis) provides ..."
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Cited by 35 (8 self)
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Abstract. Developersupplied data structure specifications are important to shape analyses, as they tell the analysis what information should be tracked in order to obtain the desired shape invariants. We observe that data structure checking code (e.g., used in testing or dynamic analysis) provides shape information that can also be used in static analysis. In this paper, we propose a lightweight, automatic shape analysis based on these developersupplied structural invariant checkers. In particular, we set up a parametric abstract domain, which is instantiated with such checker specifications to summarize memory regions using both notions of complete and partial checker evaluations. The analysis then automatically derives a strategy for canonicalizing or weakening shape invariants. 1
Configurable software verification: Concretizing the convergence of model checking and program analysis
 In Conf. on Computer Aided Verification (CAV
, 2007
"... Abstract. In automatic software verification, we have observed a theoretical convergence of model checking and program analysis. In practice, however, model checkers are still mostly concerned with precision, e.g., the removal of spurious counterexamples; for this purpose they build and refine reach ..."
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Cited by 35 (18 self)
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Abstract. In automatic software verification, we have observed a theoretical convergence of model checking and program analysis. In practice, however, model checkers are still mostly concerned with precision, e.g., the removal of spurious counterexamples; for this purpose they build and refine reachability trees. Latticebased program analyzers, on the other hand, are primarily concerned with efficiency. We designed an algorithm and built a tool that can be configured to perform not only a purely treebased or a purely latticebased analysis, but offers many intermediate settings that have not been evaluated before. The algorithm and tool take one or more abstract interpreters, such as a predicate abstraction and a shape analysis, and configure their execution and interaction using several parameters. Our experiments show that such customization may lead to dramatic improvements in the precisionefficiency spectrum. 1
Efficient state merging in symbolic execution
 In Proceedings of the ACM SIGPLAN 2012 Conference on Programming Language Design and Implementation (PLDI ’12
, 2012
"... Symbolic execution has proven to be a practical technique for building automated test case generation and bug finding tools. Nevertheless, due to state explosion, these tools still struggle to achieve scalability. Given a program, one way to reduce the number of states that the tools need to explore ..."
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Cited by 33 (2 self)
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Symbolic execution has proven to be a practical technique for building automated test case generation and bug finding tools. Nevertheless, due to state explosion, these tools still struggle to achieve scalability. Given a program, one way to reduce the number of states that the tools need to explore is to merge states obtained on different paths. Alas, doing so increases the size of symbolic path conditions (thereby stressing the underlying constraint solver) and interferes with optimizations of the exploration process (also referred to as search strategies). The net effect is that state merging may actually lower performance rather than increase it. We present a way to automatically choose when and how to merge states such that the performance of symbolic execution is significantly increased. First, we present query count estimation, a method for statically estimating the impact that each symbolic variable has on solver queries that follow a potential merge point; states are then merged only when doing so promises to be advantageous. Second, we present dynamic state merging, a technique for merging states that interacts favorably with search strategies in automated test case generation and bug finding tools. Experiments on the 96 GNU COREUTILS show that our approach consistently achieves several orders of magnitude speedup over previously published results. Our code and experimental data are publicly available at
Guided static analysis
 In Static Analysis Symp
, 2007
"... Abstract. In static analysis, the semantics of the program is expressed as a set of equations. The equations are solved iteratively over some abstract domain. If the abstract domain is distributive and satisfies the ascendingchain condition, an iterative technique yields the most precise solution f ..."
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Cited by 32 (1 self)
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Abstract. In static analysis, the semantics of the program is expressed as a set of equations. The equations are solved iteratively over some abstract domain. If the abstract domain is distributive and satisfies the ascendingchain condition, an iterative technique yields the most precise solution for the equations. However, if the above properties are not satisfied, the solution obtained is typically imprecise. Moreover, due to the properties of widening operators, the precision loss is sensitive to the order in which the statespace is explored. In this paper, we introduce guided static analysis, a framework for controlling the exploration of the statespace of a program. The framework guides the statespace exploration by applying standard staticanalysis techniques to a sequence of modified versions of the analyzed program. As such, the framework does not require any modifications to existing analysis techniques, and thus can be easily integrated into existing staticanalysis tools. We present two instantiations of the framework, which improve the precision of widening in (i) loops with multiple phases and (ii) loops in which the transformation performed on each iteration is chosen nondeterministically. 1