We present a system for extending standard type systems with flow-sensitive type qualifiers. Users annotate their programs with type qualifiers, and inference checks that the annotations are correct. In our system only the type qualifiers are modeled flow-sensitively - the underlying standard types are unchanged, which allows us to obtain an efficient constraint-based inference algorithm that integrates flow-insensitive alias analysis, effect inference, and ideas from linear type systems to support strong updates. We demonstrate the usefulness of flow-sensitive type qualifiers by finding a number of new locking bugs in the Linux kernel.

In this paper, we present a new algorithm for partial program verification that runs in polynomial time and space. We are interested in checking that a program satisfies a given temporal safety property. Our insight is that by accurately modeling only those branches in a program for which the property-related behavior differs along the arms of the branch, we can design an algorithm that is accurate enough to verify the program with respect to the given property, without paying the potentially exponential cost of full pathsensitive analysis. We have implemented this “property simulation ” algorithm as part of a partial verification tool called ESP. We present the results of applying ESP to the problem of verifying the file I/O behavior of a version of the GNU C compiler (gcc, 140,000 LOC). We are able to prove that all of the 646 calls to fprintf in the source code of gcc are guaranteed to print to valid, open files. Our results show that property simulation scales to large programs and is accurate enough to verify meaningful properties.

Ensuring the correctness of multithreaded programs is difficult, due to the potential for unexpected interactions between concurrent threads. We focus on the fundamental non-interference property of atomicity and present a dynamic analysis for detecting atomicity violations. This analysis combines ideas from both Lipton’s theory of reduction and earlier dynamic race detectors such as Eraser. Experimental results demonstrate that this dynamic atomicity analysis is effective for detecting errors due to unintended interactions between threads. In addition, the majority of methods in our benchmarks are atomic, supporting our hypothesis that atomicity is a standard methodology in multithreaded programming. 1 The Need for Atomicity Multiple threads of control are widely used in software development because they help reduce latency and provide better utilization of multiprocessor machines. However, reasoning about the correctness of multithreaded code is complicated by the nondeterministic interleaving of threads and the potential for unexpected interference between concurrent threads. Since exploring all possible interleavings of the executions of the various threads is clearly impractical, methods for specifying and controlling the interference between concurrent threads are crucial for the development of reliable multithreaded software. Much previous work on controlling thread interference has focused on race conditions, which occur when two threads simultaneously access the same data variable, and at least one of the accesses is a write [1]. Unfortunately, the absence of race conditions is not sufficient to ensure the absence of errors due to unexpected interference between threads. As a concrete illustration of

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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).

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).

Security remains a major roadblock to universal acceptance of the Web for many kinds of transactions, especially since the recent sharp increase in remotely exploitable vulnerabilities has been attributed to Web application bugs. Many verification tools are discovering previously unknown vulnerabilities in legacy C programs, raising hopes that the same success can be achieved with Web applications. In this paper, we describe a sound and holistic approach to ensuring Web application security. Viewing Web application vulnerabilities as a secure information flow problem, we created a lattice-based static analysis algorithm derived from type systems and typestate, and addressed its soundness. During the analysis, sections of code considered vulnerable are instrumented with runtime guards, thus securing Web applications in the absence of user intervention. With sufficient annotations, runtime overhead can be reduced to zero. We also created a tool named WebSSARI (Web application Security by Static Analysis and Runtime Inspection) to test our algorithm, and used it to verify 230 open-source Web application projects on SourceForge.net, which were selected to represent projects of different maturity, popularity, and scale. 69 contained vulnerabilities and their developers were notified. 38 projects acknowledged our findings and stated their plans to provide patches. Our statistics also show that static analysis reduced potential runtime overhead by 98.4%. Categories and Subject Descriptors D.2.4 [Software Engineering]: Software / Program Verification – class invariants, formal methods; D.4.6 [Operating Systems]: Security and Protection – information flow controls, correctness proofs, formal methods; K.6.5 [Computing Milieux]: Security and Protection – invasive software, unauthorized access.

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This paper shows how to use model checking to find serious errors in file systems. Model checking is a formal verification technique tuned for finding corner-case errors by comprehensively exploring the state spaces defined by a system. File systems have two dynamics that make them attractive for such an approach. First, their errors are some of the most serious, since they can destroy persistent data and lead to unrecoverable corruption. Second, traditional testing needs an impractical, exponential number of test cases to check that the system will recover if it crashes at any point during execution. Model checking employs a variety of state-reducing techniques that allow it to explore such vast state spaces efficiently. We built a system, FiSC, for model checking file systems. We applied it to three widely-used, heavily-tested file systems: ext3 [13], JFS [21], and ReiserFS [27]. We found serious bugs in all of them, 32 in total. Most have led to patches within a day of diagnosis. For each file system, FiSC found demonstrable events leading to the unrecoverable destruction of metadata and entire directories, including the file system root directory “/”. 1

This paper presents a novel framework for the symbolic bounds analysis of pointers, array indices, and accessed memory regions. Our framework formulates each analysis problem as a system of inequality constraints between symbolic bound polynomials. It then reduces the constraint system to a linear program. The solution to the linear program provides symbolic lower and upper bounds for the values of pointer and array index variables and for the regions of memory that each statement and procedure accesses. This approach eliminates fundamental problems associated with applying standard xed-point approaches to symbolic analysis problems. Experimental results from our implemented compiler show that the analysis can solve several important problems, including static race detection, automatic parallelization, static detection of array bounds violations, elimination of array bounds checks, and reduction of the number of bits used to store computed values.