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488
Compositional Model Checking
, 1999
"... We describe a method for reducing the complexity of temporal logic model checking in systems composed of many parallel processes. The goal is to check properties of the components of a system and then deduce global properties from these local properties. The main difficulty with this type of approac ..."
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Cited by 3252 (70 self)
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We describe a method for reducing the complexity of temporal logic model checking in systems composed of many parallel processes. The goal is to check properties of the components of a system and then deduce global properties from these local properties. The main difficulty with this type of approach is that local properties are often not preserved at the global level. We present a general framework for using additional interface processes to model the environment for a component. These interface processes are typically much simpler than the full environment of the component. By composing a component with its interface processes and then checking properties of this composition, we can guarantee that these properties will be preserved at the global level. We give two example compositional systems based on the logic CTL*.
Counterexample-guided Abstraction Refinement
, 2000
"... We present an automatic iterative abstraction-refinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symb ..."
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Cited by 843 (71 self)
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We present an automatic iterative abstraction-refinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symbolic techniques which analyze such counterexamples and refine the abstract model correspondingly.
The SLAM project: debugging system software via static analysis
- SIGPLAN Not
"... Abstract. The goal of the SLAM project is to check whether or not a program obeys "API usage rules " that specif[y what it means to be a good client of an API. The SLAM toolkit statically analyzes a C program to determine whether or not it violates given usage rules. The toolkit has two un ..."
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Cited by 472 (17 self)
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Abstract. The goal of the SLAM project is to check whether or not a program obeys "API usage rules " that specif[y what it means to be a good client of an API. The SLAM toolkit statically analyzes a C program to determine whether or not it violates given usage rules. The toolkit has two unique aspects: it does not require the programmer to annotate the source program (invariants are inferred); it minimizes noise (false error messages) through a process known as "counterexample-driven refinement". SLAM exploits and extends results fi'om program analysis, model checking and automated deduction.}V ~ have successfully applied the SLAM toolkit to Windows XP device drivers, to both validate behavior and find defects in their usage of kernel APIs. Context. Today, many programmers are realizing the benefits of using languages with static type systems. By providing
Automatically validating temporal safety properties of interfaces
, 2001
"... We present a process for validating temporal safety properties of software that uses a well-defined interface. The process requires only that the user state the property of interest. It then automatically creates abstractions of C code using iterative refinement, based on the given property. The pro ..."
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Cited by 433 (21 self)
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We present a process for validating temporal safety properties of software that uses a well-defined interface. The process requires only that the user state the property of interest. It then automatically creates abstractions of C code using iterative refinement, based on the given property. The process is realized in the SLAM toolkit, which consists of a model checker, predicate abstraction tool and predicate discovery tool. We have applied the SLAM toolkit to a number of Windows NT device drivers to validate critical safety properties such as correct locking behavior. We have found that the process converges on a set of predicates powerful enough to validate properties in just a few iterations. 1 Introduction Large-scale software has many components built by many programmers. Integration testing of these components is impossible or ineffective at best. Property checking of interface usage provides a way to partially validate such software. In this approach, an interface is augmented with a set of properties that all clients of the interface should respect. An automatic analysis of the client code then validates that it meets the properties, or provides examples of execution paths that violate the properties. The benefit of such an analysis is that errors can be caught early in the coding process. We are interested in checking that a program respects a set of temporal safety properties of the interfaces it uses. Safety properties are the class of properties that state that "something bad does not happen". An example is requiring that a lock is never released without first being acquired (see [24] for a formal definition). Given a program and a safety property, we wish to either validate that the code respects the property, or find an execution path that shows how the code violates the property.
Cyclone: A safe dialect of C
"... Cyclone is a safe dialect of C. It has been designed from the ground up to prevent the buffer overflows, format string attacks, and memory management errors that are common in C programs, while retaining C's syntax and semantics. This paper examines safety violations enabled by C's design ..."
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Cited by 401 (24 self)
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Cyclone is a safe dialect of C. It has been designed from the ground up to prevent the buffer overflows, format string attacks, and memory management errors that are common in C programs, while retaining C's syntax and semantics. This paper examines safety violations enabled by C's design, and shows how Cyclone avoids them, without giving up C's hallmark control over low-level details such as data representation and memory management.
Mining Specifications
, 2002
"... Program verification is a promising approach to improving program quality, because it can search all possible program executions for specific errors. However, the need to formally describe correct behavior or errors is a major barrier to the widespread adoption of program verification, since program ..."
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Cited by 366 (6 self)
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Program verification is a promising approach to improving program quality, because it can search all possible program executions for specific errors. However, the need to formally describe correct behavior or errors is a major barrier to the widespread adoption of program verification, since programmers historically have been reluctant to write formal specifications. Automating the process of formulating specifications would remove a barrier to program verification and enhance its practicality.
EXE: Automatically generating inputs of death
- In Proceedings of the 13th ACM Conference on Computer and Communications Security (CCS
, 2006
"... This article presents EXE, an effective bug-finding tool that automatically generates inputs that crash real code. Instead of running code on manually or randomly constructed input, EXE runs it on symbolic input initially allowed to be anything. As checked code runs, EXE tracks the constraints on ea ..."
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Cited by 349 (21 self)
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This article presents EXE, an effective bug-finding tool that automatically generates inputs that crash real code. Instead of running code on manually or randomly constructed input, EXE runs it on symbolic input initially allowed to be anything. As checked code runs, EXE tracks the constraints on each symbolic (i.e., input-derived) memory location. If a statement uses a symbolic value, EXE does not run it, but instead adds it as an input-constraint; all other statements run as usual. If code conditionally checks a symbolic expression, EXE forks execution, constraining the expression to be true on the true branch and false on the other. Because EXE reasons about all possible values on a path, it has much more power than a traditional runtime tool: (1) it can force execution down any feasible program path and (2) at dangerous operations (e.g., a pointer dereference), it detects if the current path constraints allow any value that causes a bug. When a path terminates or hits a bug, EXE automatically generates a test case by solving the current path constraints to find concrete values using its own co-designed constraint solver, STP. Because EXE’s constraints have no approximations, feeding this concrete input to an uninstrumented version of the checked code will cause it to follow the same path and hit the same bug (assuming deterministic code).
A Static Analyzer for Large Safety-Critical Software
, 2003
"... We show that abstract interpretation-based static program analysis can be made e#cient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. This is achieved by refinement of a general purpose static analyzer and later adaptation to p ..."
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Cited by 271 (54 self)
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We show that abstract interpretation-based static program analysis can be made e#cient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. This is achieved by refinement of a general purpose static analyzer and later adaptation to particular programs of the family by the end-user through parametrization. This is applied to the proof of soundness of data manipulation operations at the machine level for periodic synchronous safety critical embedded software. The main novelties are the design principle of static analyzers by refinement and adaptation through parametrization, the symbolic manipulation of expressions to improve the precision of abstract transfer functions, ellipsoid, and decision tree abstract domains, all with sound handling of rounding errors in floating point computations, widening strategies (with thresholds, delayed) and the automatic determination of the parameters (parametrized packing).
Modular verification of software components in C
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 2003
"... We present a new methodology for automatic verification of C programs against finite state machine specifications. Our approach is compositional, naturally enabling us to decompose the verification of large software systems into subproblems of manageable complexity. The decomposition reflects the mo ..."
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Cited by 233 (23 self)
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We present a new methodology for automatic verification of C programs against finite state machine specifications. Our approach is compositional, naturally enabling us to decompose the verification of large software systems into subproblems of manageable complexity. The decomposition reflects the modularity in the software design. We use weak simulation as the notion of conformance between the program and its specification. Following the abstractverify-refine paradigm, our tool MAGIC first extracts a finite model from C source code using predicate abstraction and theorem proving. Subsequently, simulation is checked via a reduction to Boolean satisfiability. MAGIC is able to interface with several publicly available theorem provers and SAT solvers. We report experimental results with procedures from the Linux kernel and the OpenSSL toolkit.
