Demand-Driven Memory Leak Detection Based on Flow- and Context-Sensitive Pointer Analysis

We present a demand-driven approach to memory leak detection algorithm based on flow- and context-sensitive pointer analysis. The detection algorithm firstly assumes the presence of a memory leak at some program point and then runs a backward analysis to see if this assumption can be disproved. Our algorithm computes the memory abstraction of programs based on points-to graph resulting from flow- and context-sensitive pointer analysis. We have implemented the algorithm in the SUIF2 compiler infrastructure and used the implementation to analyze a set of C benchmark programs. The experimental results show that the approach has better precision with satisfied scalability as expected. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60725206, 60673118, and 90612009, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z429, the National Basic Research 973 Program of China under Grant No. 2005CB321802, the Program for New Century Excellent Talents in University under Grant No. NCET-04-0996, and the Hunan Natural Science Foundation under Grant No. 07JJ1011.     

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

Emerging with open environments, the software paradigms, such as open resource coalition and Internetware, present several novel characteristics including user-centric, non-central control, and continual evolution. The goal of obtaining high confidence on such systems is more di?cult to achieve. The general developer-oriented metrics and testing-based methods which are adopted in the traditional measurement for high confidence software seem to be infeasible in the new situation. Firstly, the software develo...     

Integrating Scene Parallelism in Camera Auto-Calibration

This paper presents an approach for camera auto-calibration from uncalibrated video sequences taken by a hand-held camera.The novelty of this approach lies in that the line parallelism is transformed to the constraints on the absolute quadric during camera autocalibration.This makes some critical cases solvable and the reconstruction more Euclidean.The approach is implemented and validated using simulated data and real image data.The experimental results show the effectiveness of the approach.     

Coding-based Join Algorithms for Structural Queries on Graph-Structured XML Document

In many applications, XML documents need to be modelled as graphs. The query processing of graph-structured XML documents brings new challenges. In this paper, we design a method based on labelling scheme for structural queries processing on graph-structured XML documents. We give each node some labels, the reachability labelling scheme. By extending an interval-based reachability labelling scheme for DAG by Rakesh et al., we design labelling schemes to support the judgements of reachability relationships for general graphs. Based on the labelling schemes, we design graph structural join algorithms to answer the structural queries with only ancestor-descendant relationship efficiently. For the processing of subgraph query, we design a subgraph join algorithm. With efficient data structure, the subgraph join algorithm can process subgraph queries with various structures efficiently. Experimental results show that our algorithms have good performance and scalability. Support by the Key Program of the National Natural Science Foundation of China under Grant No.60533110; the National Grand Fundamental Research 973 Program of China under Grant No. 2006CB303000; the National Natural Science Foundation of China under Grant No. 60773068 and No. 60773063.     

A Real-Time Performance Evaluation Model for Distributed Software with Reliability Constrains

In this paper, we propose an approach for the real-time performance analysis of distributed software with reliability constraints, called Athena. The approach is based on the real-time and reliability performance analysis of distributed program. In Athena, two important factors, imperfect nodes and the links reliability, are introduced. The algorithms proposed in Athena generates sub-graphs, counts the reliability of each sub-graph, calculates the transmission time for all the transmission paths of each data file, and computes response time of each data file with reliability constraint. In this way, the real-time performance of distributed software with reliability constrains can be evaluated.This paper is supported by National Science Foundation of China under grant 60273076.     

A moving object segmentation algorithm for static camera via active contours and GMM

Moving object segmentation is one of the most challenging issues in computer vision. In this paper, we propose a new algorithm for static camera foreground segmentation. It combines Gaussian mixture model (GMM) and active contours method, and produces much better results than conventional background subtraction methods. It formulates foreground segmentation as an energy minimization problem and minimizes the energy function using curve evolution method. Our algorithm integrates the GMM background model, shadow elimination term and curve evolution edge stopping term into energy function. It achieves more accurate segmentation than existing methods of the same type. Promising results on real images demonstrate the potential of the presented method. Supported by National Basic Research Program of China (Grant No. 2006CB303105), the Chinese Ministry of Education Innovation Team Fund Project (Grant No. IRT0707), the National Natural Science Foundation of China (Grant Nos. 60673109 and 60801053), Beijing Excellent Doctoral Thesis Program (Grant No. YB20081000401), Beijing Municipal Natural Science Foundation (Grant No. 4082025), and Doctoral Foundation of China (Grant No. 20070004037)     

Measuring class cohesion based on dependence analysis

Classes are the basic modules in object-oriented (OO) software, which consist of attributes and methods. Thus, in OO environment, the cohesion is mainly about the tightness of the attributes and methods of classes. This paper discusses the relationships between attributes and attributes, attributes and methods,methods and methods of a class based on dependence analysis. Then the paper presents methods to compute these dependencies. Based on these, the paper proposes a method to measure the class cohesion, which satisfies the properties that a good measurement should have. The approach overcomes the limitations of previous class cohesion measures, which consider only one or two of the three relationships in a class.     

Pose estimation based on human detection and segmentation

We address the problem of 3D human pose estimation in a single real scene image. Normally, 3D pose estimation from real image needs background subtraction to extract the appropriate features. We do not make such assumption. In this paper, a two-step approach is proposed, first, instead of applying background subtraction to get the segmentation of human, we combine the segmentation with human detection using an ISM-based detector. Then, silhouette feature can be extracted and 3D pose estimation is solved as a regression problem. RVMs and ridge regression method are applied to solve this problem. The results show the robustness and accuracy of our method. Supported by the National Basic Research Program of China (Grant No. 2006CB303103), and Key Program of the National Natural Science Foundation of China (Grant No. 60833009)     

Steady-state performance analysis of HOS-based blind adaptive multiuser detection

The blind adaptive multiuser detections based on higher-order statistics (HOS) can obtain higher steady-state decorrelating performance than the conventional linear algorithm under the high SNR condition. However, the closed-form analysis for this steady-state performance is scarce due to the complication of analyzing the nonlinear updates of the adaptive algorithm. An analysis approach based on ordinary differential equation (ODE) method is proposed to get the closed-form excess mean-square error (EMSE) expression of the HOS-based multiuser detections. The simulation and the comparison verify the results of the analysis. Supported by the National Natural Science Foundation of China (Grant No. 60432040), and the Guangxi Natural Science Foundation (Grant Nos. 0731026, 0731025)     

A formal method to real-time protocol interoperability testing

Interoperability testing is an important technique to ensure the quality of implementations of network communication protocol. In the next generation Internet protocol, real-time applications should be supported effectively. However, time constraints were not considered in the related studies of protocol interoperability testing, so existing interoperability testing methods are difficult to be applied in real-time protocol interoperability testing. In this paper, a formal method to real-time protocol interoperability testing is proposed. Firstly, a formal model CMpTIOA （communicating multi-port timed input output automata） is defined to specify the system under test （SUT） in real-time protocol interoperability testing; based on this model, timed interoperability relation is then defined. In order to check this relation, a test generation method is presented to generate a parameterized test behavior tree from SUT model; a mechanism of executability pre-determination is also integrated in the test generation method to alleviate state space explosion problem to some extent. The proposed theory and method are then applied in interoperability testing of IPv6 neighbor discovery protocol to show the feasibility of this method.     

基于目标制导符号执行的静态缓冲区溢出警报自动确认技术

缓冲区溢出漏洞是一类严重的安全性缺陷。目前存在动态测试和静态分析技术来检测缓冲区溢出缺陷:动态测试技术的有效性取决于测试用例的设计,而且往往会引入执行开销;静态分析技术及自动化工具已经被广泛运用于缓冲区溢出缺陷检测中,然而静态分析由于采取了保守的策略,其结果往往包含数量巨大的误报,需要通过进一步人工确认来甄别误报,但人工确认静态分析的结果耗时且容易出错,严重限制了静态分析技术的实用性。符号执行技术使用符号代替实际输入,能系统地探索程序的状态空间并生成高覆盖度的测试用例。本文提出一种基于目标制导符号执行的静态缓冲区溢出警报确认方法,使用静态分析工具的输出结果作为目标,制导符号执行确认警报。我们的方法分为3步:首先在过程间控制流图中检测静态分析警报路径片段的可达性,并将可达的警报路径片段集合映射为用于确认的完整确认路径集合;其次在符号执行中通过修剪与溢出缺陷疑似语句无关的路径,指导符号执行沿特定确认路径执行;最后在溢出缺陷疑似语句收集路径约束并加入溢出条件,通过约束求解的结果,对静态分析的警报进行分类。基于上述方法我们实现了原型工具BOVTool,实验结果表明在实际开源程序上BOVTool能够代替人工减少检查59.9%的缓冲区溢出误报。     

A digital authentication watermarking scheme for JPEG images with superior localization and security

The drawbacks of the current authentication watermarking schemes for JPEG images, which are inferior localization and the security flaws, are firstly analyzed in this paper. Then, two counterferiting attacks are conducted on them. To overcome these drawbacks, a new digital authentication watermarking scheme for JPEG images with superior localization and security is proposed. Moreover, the probabilities of tamper detection and false detection are deduced under region tampering and collage attack separately. For each image block, the proposed scheme keeps four middle frequency points fixed to embed the watermark, and utilizes the rest of the DCT coefficients to generate 4 bits of watermark information. During the embedding process, each watermark bit is embedded in another image block that is selected by its corresponding secret key. Since four blocks are randomly selected for the watermark embedding of each block, the non-deterministic dependence among the image blocks is established so as to resist collage attack completely. At the receiver, according to judging of the extracted 4 bits of watermark information and the corresponding 9-neighbourhood system, the proposed scheme could discriminate whether the image block is tampered or not. Owing to the diminishing of false detection and the holding of tamper detection, we improve the accuracy of localization in the authentication process. Theoretic analysis and simulation results have proved that the proposed algorithm not only has superior localization, but also enhances the systematic security obviously. Supported by the National Natural Science Foundation of China (Grant No. 60572027), the Program for New Century Excellent Talents in University of China (Grant No. NCET-05-0794), the Sichuan Youth Science & Technology Foundation (Grant No. 03ZQ026-033), the National Defense Pre-research Foundation of China (Grant No. 51430804QT2201) and the Application Basic Foundation of Sichuan Province, China (Grant No. 2006 J13-10)     

Min-max model predictive control for constrained nonlinear systems via multiple LPV embeddings

A min-max model predictive control strategy is proposed for a class of constrained nonlinear system whose trajectories can be embedded within those of a bank of linear parameter varying (LPV) models. The embedding LPV models can yield much better approximation of the nonlinear system dynamics than a single LTV model. For each LPV model, a parameter-dependent Lyapunov function is introduced to obtain poly-quadratically stable control law and to guarantee the feasibility and stability of the original nonlinear system. This approach can greatly reduce computational burden in traditional nonlinear predictive control strategy. Finally a simulation example illustrating the strategy is presented. Supported by the National Natural Science Foundation of China (Grant Nos. 60774015, 60825302, 60674018), the National High-Tech Research & Development Program of China (Grant No. 2007AA041403), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20060248001), and partly by Shanghai Natural Science Foundation (Grant No. 07JC14016)     

IETF softwire unicast and multicast framework for IPv6 transition

IPv6 protocol plays an important role in the next generation of Internet （NGI）. It is expected that the elegant coexistence of IPv4 and IPv6 is the key point of IPv6 transition. To solve the transition problem, we propose a mesh unicast framework and a multicast framework in this paper. We describe two reference models for the mesh unicast framework, and put forward two potential solutions for the multicast framework. A Linux-based prototype is implemented for IPv4 over IPv6 scenario and a test bed is deployed with 8 nodes on CERNET2. The deployment demon- strates the advantages of the framework.     

Algebraic properties on the cuts of lattice-valued regular languages

In this paper, the algebraic operations on the cuts of lattice-valued regular languages are studied. Some sufficient conditions are given to guarantee the family of the cuts of lattice-valued regular languages to be closed under such algebraic operations as union, intersection, complement, quotient, homomorphism, inverse homomorphism, concatennation, reversal, etc. This work is supported by National Science Foundation of China (Grant No.10571112), “TRAPOYT” of China and National 973 Foundation Research Program (Grant No. 2002CB312200).     

A 485ps 64-Bit Parallel Adder in 0.18$\mu$m CMOS

This paper presents an optimized 64-bit parallel adder. Sparse-tree architecture enables low carry-merge fan-outs and inter-stage wiring complexity. Single-rail and semi-dynamic circuit improves operation speed. Simulation results show that the proposed adder can operate at 485ps with power of 25.6mW in 0.18μm CMOS process. It achieves the goal of higher speed and lower power.     

Estimating differential quantities from point cloud based on a linear fitting of normal vectors

Estimation of differential geometric properties on a discrete surface is a fundamental work in computer graphics and computer vision. In this paper, we present an accurate and robust method for estimating differential quantities from unorganized point cloud. The principal curvatures and principal directions at each point are computed with the help of partial derivatives of the unit normal vector at that point, where the normal derivatives are estimated by fitting a linear function to each component of the normal vectors in a neighborhood. This method takes into account the normal information of all neighboring points and computes curvatures directly from the variation of unit normal vectors, which improves the accuracy and robustness of curvature estimation on irregular sampled noisy data. The main advantage of our approach is that the estimation of curvatures at a point does not rely on the accuracy of the normal vector at that point, and the normal vectors can be refined in the process of curvature estimation. Compared with the state of the art methods for estimating curvatures and Darboux frames on both synthetic and real point clouds, the approach is shown to be more accurate and robust for noisy and unorganized point cloud data. Supported in part by the National Natural Science Foundation of China (Grant Nos. 60672148, 60872120), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z301, 2008AA01Z301), and Beijing Municipal Natural Science Foundation (Grant No. 4062033)     

Neural Network Algorithm for Designing FIR Filters Utilizing Frequency-Response Masking Technique

This paper presents a new joint optimization method for the design of sharp linear-phase finite-impulse response (FIR) digital filters which are synthesized by using basic and multistage frequency-response-masking(FRM) techniques.The method is based on a batch back-propagation neural network algorithm with a variable learning rate mode.We propose the following two-step optimization technique in order to reduce the complexity.At the first step,an initial FRM filter is designed by alternately optimizing th...     

SKY: efficient peer-to-peer networks based on distributed Kautz graphs

Many proposed P2P networks are based on traditional interconnection topologies. Given a static topology, the maintenance mechanism for node join/departure is critical to designing an efficient P2P network. Kautz graphs have many good properties such as constant degree, low congestion and optimal diameter. Due to the complexity in topology maintenance, however, to date there have been no effective P2P networks that are proposed based on Kautz graphs with base > 2. To address this problem, this paper presents the “distributed Kautz (D-Kautz) graphs”, which adapt Kautz graphs to the characteristics of P2P networks. Using the D-Kautz graphs we further propose SKY, the first effective P2P network based on Kautz graphs with arbitrary base. The effectiveness of SKY is demonstrated through analysis and simulations. Supported partially by the National Natural Science Foundation of China (Grant Nos. 60673167 and 60703072), the Hunan Provincial Natural Science Foundation of China (Grant No. 08JJ3125), and the National Basic Research Program of China (973) (Grant No. 2005CB321801)     

Removing local irregularities of triangular meshes with highlight line models

The highlight line model is a powerful tool in assessing the quality of a surface. It increases the flexibility of an interactive design environment. In this paper, a method to generate a highlight line model on an arbitrary triangular mesh is presented. Based on the highlight line model, a technique to remove local shape irregularities of a triangular mesh is then presented. The shape modification is done by solving a minimization problem and performing an iterative procedure. The new technique improves not only the shape quality of the mesh surface, but also the shape of the highlight line model. It provides an intuitive and yet suitable method for locally optimizing the shape of a triangular mesh. Supported by National Science Foundation of China (Grant Nos. 60533070, 60625202), National Basic Research Program of China (Grant No. 2004CB719400), National High-Tech Research & Development Program of China (Grant No. 2007AA040401), Fok Ying Tung Education Foundation (Grant No. 111070), National Science Foundation of USA (Grant Nos. DMI-0422126, DMS-0310645), and Kentucky Science & Technology Corporation (Grant No. COMM-Fund-712)