11714898
On the number of limit cycles of a cubic polynomials Hamiltonian system under quintic perturbation
Abstract This paper is concerned with the number and distribution of limit cycles of a cubic Hamiltonian system under quintic perturbation. By using the bifurcation theory and the method of detection function, we obtain that this system exists at least 14 limit cycles with the distribution C 9 1 ⊃ [ C 1 1 + 2 ( C 3 2 ⊃ 2 C 1 2 ) ] . These results in the paper are useful for the study of the weakened Hilbert’s 16th problem.
29892228
Bifurcations of traveling wave solutions for a class of the generalized Benjamin-Bona-Mahony equation
Abstract By using the theory of bifurcations of dynamical systems to a class of the generalized Benjamin–Bona–Mahony (GBBM) equation, the existence of solitary wave solutions and uncountably infinite, many smooth and non-smooth periodic wave solutions are obtained. It can be shown that the existence of singular curves in a traveling wave system is the reason why smooth waves converge to cusp waves, finally. When parameters are varied, under different parametric conditions, various sufficient conditions to guarantee the existence of the above solutions are given.
9372724
Provably Correct Runtime Enforcement of Non-interference Properties
Non-interference has become the standard criterion for ensuring confidentiality of sensitive data in the information flow literature. However, application of non-interference to practical software systems has been limited. This is partly due to the imprecision that is inherent in static analyses that have formed the basis of previous non-interference based techniques. Runtime approaches can be significantly more accurate than static analysis, and have often been more successful in practice. However, they can only reason about explicit information flows that take place via assignments in a program. Implicit flows that take place without involving assignments, and can be inferred from the structure and/or semantics of the program, are missed by runtime techniques. This paper seeks to bridge the gap between the accuracy provided by runtime techniques and the completeness provided by static analysis techniques. In particular, we develop a hybrid technique that relies primarily on runtime information-flow tracking, but augments it with static analysis to reason about implicit flows that arise due to unexecuted paths in a program. We prove that the resulting technique preserves non-interference, while providing some of the traditional benefits of dynamic analysis such as improved accuracy.
17469824
Extending OBDD graphs for composite event matching in content-based pub/sub systems
Content-based publish/subscribe offers a convenient abstraction for the information producers and consumers, supporting a large-scale system design and evolution by integrating several distributed independent application systems. Its core problem is how to match events by predicates on the content of events. In this paper, we propose three matching models, extend the simple matching to the multi-semantic matching and introduce the temporal constraint variable. The multi-semantic matching allows using different operations in accordance with different semantics; the temporal constraint variable supports processing the discrete events in the temporal sequence. Then, we extend OBDD graphs into hierarchy coloured OBDD graphs and prove the equivalence of the transformation. At last, based on OBDD graphs the composite matching algorithm is presented and analysed. By experiments, we show the proposed algorithm is efficient.
14513289
Mining Console Logs for Large-Scale System Problem Detection
The console logs generated by an application contain messages that the application developers believed would be useful in debugging or monitoring the application. Despite the ubiquity and large size of these logs, they are rarely exploited in a systematic way for monitoring and debugging because they are not readily machine-parsable. In this paper, we propose a novel method for mining this rich source of information. First, we combine log parsing and text mining with source code analysis to extract structure from the console logs. Second, we extract features from the structured information in order to detect anomalous patterns in the logs using Principal Component Analysis (PCA). Finally, we use a decision tree to distill the results of PCA-based anomaly detection to a format readily understandable by domain experts (e.g. system operators) who need not be familiar with the anomaly detection algorithms. As a case study, we distill over one million lines of console logs from the Hadoop file system to a simple decision tree that a domain expert can readily understand; the process requires no operator intervention and we detect a large portion of runtime anomalies that are commonly overlooked.
156293
An efficient and backwards-compatible transformation to ensure memory safety of C programs
Memory-related errors, such as buffer overflows and dangling pointers, remain one of the principal reasons for failures of C programs. As a result, a number of recent research efforts have focused on the problem of dynamic detection of memory errors in C programs. However, existing approaches suffer from one or more of the following problems: inability to detect all memory errors (e.g., Purify), requiring non-trivial modifications to existing C programs (e.g., Cyclone), changing the memory management model of C to use garbage collection (e.g., CCured), and excessive performance overheads. In this paper, we present a new approach that addresses these problems. Our approach operates via source code transformation and combines efficient data-structures with simple, localized optimizations to obtain good performance.
7039845
An Algorithm for Solving Scaled Total Least Squares Problems
In this paper, we present a rankrevealing two-sided orthogonal decomposition method for solving the STLS problem. An error analysis of the algorithm is given. Our numerical experiments show that this algorithm computes the STLS solution as accurate as the SVD method with less computation.