1,757 research outputs found

    Particle-based and Meshless Methods with Aboria

    Full text link
    Aboria is a powerful and flexible C++ library for the implementation of particle-based numerical methods. The particles in such methods can represent actual particles (e.g. Molecular Dynamics) or abstract particles used to discretise a continuous function over a domain (e.g. Radial Basis Functions). Aboria provides a particle container, compatible with the Standard Template Library, spatial search data structures, and a Domain Specific Language to specify non-linear operators on the particle set. This paper gives an overview of Aboria's design, an example of use, and a performance benchmark

    Dynamic Race Prediction in Linear Time

    Full text link
    Writing reliable concurrent software remains a huge challenge for today's programmers. Programmers rarely reason about their code by explicitly considering different possible inter-leavings of its execution. We consider the problem of detecting data races from individual executions in a sound manner. The classical approach to solving this problem has been to use Lamport's happens-before (HB) relation. Until now HB remains the only approach that runs in linear time. Previous efforts in improving over HB such as causally-precedes (CP) and maximal causal models fall short due to the fact that they are not implementable efficiently and hence have to compromise on their race detecting ability by limiting their techniques to bounded sized fragments of the execution. We present a new relation weak-causally-precedes (WCP) that is provably better than CP in terms of being able to detect more races, while still remaining sound. Moreover it admits a linear time algorithm which works on the entire execution without having to fragment it.Comment: 22 pages, 8 figures, 1 algorithm, 1 tabl

    Deciding Quantifier-Free Presburger Formulas Using Parameterized Solution Bounds

    Full text link
    Given a formula in quantifier-free Presburger arithmetic, if it has a satisfying solution, there is one whose size, measured in bits, is polynomially bounded in the size of the formula. In this paper, we consider a special class of quantifier-free Presburger formulas in which most linear constraints are difference (separation) constraints, and the non-difference constraints are sparse. This class has been observed to commonly occur in software verification. We derive a new solution bound in terms of parameters characterizing the sparseness of linear constraints and the number of non-difference constraints, in addition to traditional measures of formula size. In particular, we show that the number of bits needed per integer variable is linear in the number of non-difference constraints and logarithmic in the number and size of non-zero coefficients in them, but is otherwise independent of the total number of linear constraints in the formula. The derived bound can be used in a decision procedure based on instantiating integer variables over a finite domain and translating the input quantifier-free Presburger formula to an equi-satisfiable Boolean formula, which is then checked using a Boolean satisfiability solver. In addition to our main theoretical result, we discuss several optimizations for deriving tighter bounds in practice. Empirical evidence indicates that our decision procedure can greatly outperform other decision procedures.Comment: 26 page

    A Survey of Symbolic Execution Techniques

    Get PDF
    Many security and software testing applications require checking whether certain properties of a program hold for any possible usage scenario. For instance, a tool for identifying software vulnerabilities may need to rule out the existence of any backdoor to bypass a program's authentication. One approach would be to test the program using different, possibly random inputs. As the backdoor may only be hit for very specific program workloads, automated exploration of the space of possible inputs is of the essence. Symbolic execution provides an elegant solution to the problem, by systematically exploring many possible execution paths at the same time without necessarily requiring concrete inputs. Rather than taking on fully specified input values, the technique abstractly represents them as symbols, resorting to constraint solvers to construct actual instances that would cause property violations. Symbolic execution has been incubated in dozens of tools developed over the last four decades, leading to major practical breakthroughs in a number of prominent software reliability applications. The goal of this survey is to provide an overview of the main ideas, challenges, and solutions developed in the area, distilling them for a broad audience. The present survey has been accepted for publication at ACM Computing Surveys. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5FvcComment: This is the authors pre-print copy. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5Fv

    Early Packet Rejection Using Dynamic Binary Decision Diagram

    Get PDF
    A firewall is a hardware or software device that performs inspection on a given incoming/outgoing packets and decide whether to allow/deny the packet from entering/leaving the system. Firewall filters the packets by using a set of rules called firewall policies. The policies define what type of packets should be allowed or discarded. These policies describe the field values that the packet header must contain in order to match a policy in the firewall. The decision for any given packet is made by finding the first matching firewall policy, if any. In a traditional firewall, the packet filter goes through each policy in the list until a matching rule is found; the same process is again repeated for every packet that enters the firewall. The sequential lookup that the firewall uses to find the matching rule is time consuming and the total time it takes to perform the lookup increases as the policy in the list increases. Nowadays, a typical enterprise based firewall will have 1000+ firewall policy in it, which is normal. A major threat to network firewalls is specially crafted malicious packets that target the bottom rules of the firewall’s entire set of filtering rules. This attack’s main objective is to overload the firewall by processing a flood of network traffic that is matched against almost all the filtering rules before it gets rejected by a bottom rule. As a consequence of this malicious flooding network traffic, the firewall performance will decrease and the processing time of network traffic may increase significantly The current research work is based on the observation that an alternative method for the firewall policies can provide a faster lookup and hence a better filtering performance. The method proposed in this research relies on a basic fact that the policy c a n be represented as a simple Boolean expression. Thus, Binary Decision Diagrams (BDDs) are used as a basis for the representation of access list in this study. The contribution of this research work is a proposed method for representing firewall Policies using BDDs to improve the performance of packet filtering. The proposed mechanism is called Static Shuffling Binary Decision Diagram (SS-BDD), and is based on restructuring of the Binary Decision Diagram (BDD) by using byte-wise data structure instead of using Field-wise data structure. Real world traffic is used during the simulation phase to prove the performance of packet filtering. The numerical results obtained by the simulation shows that the proposed technique improves the performance for packet filtering significantly on medium to long access lists. Furthermore, using BDDs for representing the firewall policies provides other Useful characteristics that makes this a beneficial approach to in real world
    • …
    corecore