2,781 research outputs found

    Array bounds check elimination in the context of deoptimization

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    AbstractWhenever an array element is accessed, Java virtual machines execute a compare instruction to ensure that the index value is within the valid bounds. This reduces the execution speed of Java programs. Array bounds check elimination identifies situations in which such checks are redundant and can be removed. We present an array bounds check elimination algorithm for the Java HotSpot™ VM based on static analysis in the just-in-time compiler.The algorithm works on an intermediate representation in static single assignment form and maintains conditions for index expressions. It fully removes bounds checks if it can be proven that they never fail. Whenever possible, it moves bounds checks out of loops. The static number of checks remains the same, but a check inside a loop is likely to be executed more often. If such a check fails, the executing program falls back to interpreted mode, avoiding the problem that an exception is thrown at the wrong place.The evaluation shows a speedup near to the theoretical maximum for the scientific SciMark benchmark suite and also significant improvements for some Java Grande benchmarks. The algorithm slightly increases the execution speed for the SPECjvm98 benchmark suite. The evaluation of the DaCapo benchmarks shows that array bounds checks do not have a significant impact on the performance of object-oriented applications

    Transfer Function Synthesis without Quantifier Elimination

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    Traditionally, transfer functions have been designed manually for each operation in a program, instruction by instruction. In such a setting, a transfer function describes the semantics of a single instruction, detailing how a given abstract input state is mapped to an abstract output state. The net effect of a sequence of instructions, a basic block, can then be calculated by composing the transfer functions of the constituent instructions. However, precision can be improved by applying a single transfer function that captures the semantics of the block as a whole. Since blocks are program-dependent, this approach necessitates automation. There has thus been growing interest in computing transfer functions automatically, most notably using techniques based on quantifier elimination. Although conceptually elegant, quantifier elimination inevitably induces a computational bottleneck, which limits the applicability of these methods to small blocks. This paper contributes a method for calculating transfer functions that finesses quantifier elimination altogether, and can thus be seen as a response to this problem. The practicality of the method is demonstrated by generating transfer functions for input and output states that are described by linear template constraints, which include intervals and octagons.Comment: 37 pages, extended version of ESOP 2011 pape

    Everything You Want to Know About Pointer-Based Checking

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    Lack of memory safety in C/C++ has resulted in numerous security vulnerabilities and serious bugs in large software systems. This paper highlights the challenges in enforcing memory safety for C/C++ programs and progress made as part of the SoftBoundCETS project. We have been exploring memory safety enforcement at various levels - in hardware, in the compiler, and as a hardware-compiler hybrid - in this project. Our research has identified that maintaining metadata with pointers in a disjoint metadata space and performing bounds and use-after-free checking can provide comprehensive memory safety. We describe the rationale behind the design decisions and its ramifications on various dimensions, our experience with the various variants that we explored in this project, and the lessons learned in the process. We also describe and analyze the forthcoming Intel Memory Protection Extensions (MPX) that provides hardware acceleration for disjoint metadata and pointer checking in mainstream hardware, which is expected to be available later this year

    Multi-Paradigm Metric and its Applicability on JAVA Projects

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    JAVA is one of the favorite languages amongst software developers. However, the numbers of specific software metrics to evaluate the JAVA code are limited. In this paper, we evaluate the applicability of a recently developed multi paradigm metric to JAVA projects. The experimentations show that the Multi paradigm metric is an effective measure for estimating the complexity of the JAVA code/projects, and therefore it can be used for controlling the quality of the projects. We have also evaluated the multi-paradigm metric against the principles of measurement theory

    A programming logic for Java bytecode programs

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    One significant disadvantage of interpreted bytecode languages, such as Java, is their low execution speed in comparison to compiled languages like C. The mobile nature of bytecode adds to the problem, as many checks are necessary to ensure that downloaded code from untrusted sources is rendered as safe as possible. But there do exist ways of speeding up such systems. One approach is to carry out static type checking at load time, as in the case of the Java Bytecode Verifier. This reduces the number of runtime checks that must be done and also allows certain instructions to be replaced by faster versions. Another approach is the use of a Just In Time (JIT) Compiler, which takes the bytecode and produces corresponding native code at runtime. Some JIT compilers also carry out some code optimization. There are, however, limits to the amount of optimization that can safely be done by the Verifier and JITs; some operations simply cannot be carried out safely without a certain amount of runtime checking. But what if it were possible to prove that the conditions the runtime checks guard against would never arise in a particular piece of code? In this case it might well be possible to dispense with these checks altogether, allowing optimizations not feasible at present. In addition to this, because of time constraints, current JIT compilers tend to produce acceptable code as quickly as possible, rather than producing the best code possible. By removing the burden of analysis from them it may be possible to change this. We demonstrate that it is possible to define a programming logic for bytecode programs that allows the proof of bytecode programs containing loops. The instructions available to use in the programs are currently limited, but the basis is in place to extend these. The development of this logic is non-trivial and addresses several difficult problems engendered by the unstructured nature of bytecode programs

    The C++0x "Concepts" Effort

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    C++0x is the working title for the revision of the ISO standard of the C++ programming language that was originally planned for release in 2009 but that was delayed to 2011. The largest language extension in C++0x was "concepts", that is, a collection of features for constraining template parameters. In September of 2008, the C++ standards committee voted the concepts extension into C++0x, but then in July of 2009, the committee voted the concepts extension back out of C++0x. This article is my account of the technical challenges and debates within the "concepts" effort in the years 2003 to 2009. To provide some background, the article also describes the design space for constrained parametric polymorphism, or what is colloquially know as constrained generics. While this article is meant to be generally accessible, the writing is aimed toward readers with background in functional programming and programming language theory. This article grew out of a lecture at the Spring School on Generic and Indexed Programming at the University of Oxford, March 2010

    Muggl: The Muenster Generator of Glass-box Test Cases

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    Testing is a task that requires much effort, yet it is essential for developing software. Automated test case generation (TCG) promises to relieve humans of manual work. We introduce Muggl (the Muenster generator of glass-box test cases), which is developed at our institute. Muggl generates test cases for Java bytecode. It symbolically executes code and uses constraint solving techniques. While papers on Muggl have already been published, no comprehensive introduction of the tool exist. This working paper fills this gap

    Development of a static analysis tool to find securty vulnerabilities in java applications

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    Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2010Includes bibliographical references (leaves: 57-60)Text in English Abstract: Turkish and Englishix, 77 leavesThe scope of this thesis is to enhance a static analysis tool in order to find security limitations in java applications. This will contribute to the removal of some of the existing limitations related with the lack of java source codes. The generally used tools for a static analysis are FindBugs, Jlint, PMD, ESC/Java2, Checkstyle. In this study, it is aimed to utilize PMD static analysis tool which already has been developed to find defects Possible bugs (empty try/catch/finally/switch statements), Dead code (unused local variables, parameters and private methods), Suboptimal code (wasteful String/StringBuffer usage), Overcomplicated expressions (unnecessary if statements for loops that could be while loops), Duplicate code (copied/pasted code means copied/pasted bugs). On the other hand, faults possible unexpected exception, length may be less than zero, division by zero, stream not closed on all paths and should be a static inner class cases were not implemented by PMD static analysis tool. PMD performs syntactic checks and dataflow analysis on program source code.In addition to some detection of clearly erroneous code, many of the .bugs. PMD looks for are stylistic conventions whose violation might be suspicious under some circumstances. For example, having a try statement with an empty catch block might indicate that the caught error is incorrectly discarded. Because PMD includes many detectors for bugs that depend on programming style, PMD includes support for selecting which detectors or groups of detectors should be run. While PMD.s main structure was conserved, boundary overflow vulnerability rules have been implemented to PMD
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