645 research outputs found

    Parameterized Construction of Program Representations for Sparse Dataflow Analyses

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    Data-flow analyses usually associate information with control flow regions. Informally, if these regions are too small, like a point between two consecutive statements, we call the analysis dense. On the other hand, if these regions include many such points, then we call it sparse. This paper presents a systematic method to build program representations that support sparse analyses. To pave the way to this framework we clarify the bibliography about well-known intermediate program representations. We show that our approach, up to parameter choice, subsumes many of these representations, such as the SSA, SSI and e-SSA forms. In particular, our algorithms are faster, simpler and more frugal than the previous techniques used to construct SSI - Static Single Information - form programs. We produce intermediate representations isomorphic to Choi et al.'s Sparse Evaluation Graphs (SEG) for the family of data-flow problems that can be partitioned per variables. However, contrary to SEGs, we can handle - sparsely - problems that are not in this family

    Validation of Memory Accesses Through Symbolic Analyses

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    International audienceThe C programming language does not prevent out-of- bounds memory accesses. There exist several techniques to secure C programs; however, these methods tend to slow down these programs substantially, because they populate the binary code with runtime checks. To deal with this prob- lem, we have designed and tested two static analyses - sym- bolic region and range analysis - which we combine to re- move the majority of these guards. In addition to the analy- ses themselves, we bring two other contributions. First, we describe live range splitting strategies that improve the effi- ciency and the precision of our analyses. Secondly, we show how to deal with integer overflows, a phenomenon that can compromise the correctness of static algorithms that validate memory accesses. We validate our claims by incorporating our findings into AddressSanitizer. We generate SPEC CINT 2006 code that is 17% faster and 9% more energy efficient than the code produced originally by this tool. Furthermore, our approach is 50% more effective than Pentagons, a state- of-the-art analysis to sanitize memory accesses

    Improving Quality of Software with Foreign Function Interfaces using Static Analysis

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    A Foreign Function Interface (FFI) is a mechanism that allows software written in one host programming language to directly use another foreign programming language by invoking function calls across language boundaries. Today\u27s software development often utilizes FFIs to reuse software components. Examples of such systems are the Java Development Kit (JDK), Android mobile OS, and Python packages in the Fedora LINUX operating systems. The use of FFIs, however, requires extreme care and can introduce undesired side effects that degrade software quality. In this thesis, we aim to improve several quality aspects of software composed of FFIs by applying static analysis. The thesis investigates several particular characteristics of FFIs and studies software bugs caused by the misuse of FFIs. We choose two FFIs, the Java Native Interface (JNI) and the Python/C interface, as the main subjects of this dissertation. To reduce software security vulnerabilities introduced by the JNI, we first propose definitions of new patterns of bugs caused by the improper exception handlings between Java and C. We then present the design and implement a bug finding system to uncover these bugs. To ensure software safety and reliability in multithreaded environment, we present a novel and efficient system that ensures atomicity in the JNI. Finally, to improve software performance and reliability, we design and develop a framework for finding errors in memory management in programs written with the Python/C interface. The framework is built by applying affine abstraction and affine analysis of reference-counts of Python objects. This dissertation offers a comprehensive study of FFIs and software composed of FFIs. The research findings make several contributions to the studies of static analysis and to the improvement of software quality

    Abstract Model Counting: A Novel Approach for Quantification of Information Leaks

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    acmid: 2590328 keywords: model checking, quantitative information flow, satisfiability modulo theories, symbolic execution location: Kyoto, Japan numpages: 10acmid: 2590328 keywords: model checking, quantitative information flow, satisfiability modulo theories, symbolic execution location: Kyoto, Japan numpages: 10acmid: 2590328 keywords: model checking, quantitative information flow, satisfiability modulo theories, symbolic execution location: Kyoto, Japan numpages: 10We present a novel method for Quantitative Information Flow analysis. We show how the problem of computing information leakage can be viewed as an extension of the Satisfiability Modulo Theories (SMT) problem. This view enables us to develop a framework for QIF analysis based on the framework DPLL(T) used in SMT solvers. We then show that the methodology of Symbolic Execution (SE) also fits our framework. Based on these ideas, we build two QIF analysis tools: the first one employs CBMC, a bounded model checker for ANSI C, and the second one is built on top of Symbolic PathFinder, a Symbolic Executor for Java. We use these tools to quantify leaks in industrial code such as C programs from the Linux kernel, a Java tax program from the European project HATS, and anonymity protocol
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