基于UML模型和OCL约束的类间交互测试用例生成方法研究

 面向对象所具有的类、封装、继承、动态连接等特性,使得面向对象测试步骤的划分以及测试策略的选择有别于传统的测试思想.本文针对面向对象软件的特点,采用基于模型的软件测试方法,对UML(United Model Language)设计模型中的顺序图添加OCL(Object Constraints Language)约束,做类间交互的软件测试.本文提出执行图EG生成算法,将顺序图SD转换为执行图EG,解决UML2.0顺序图新增特性中的alt、loop、opt、break四种常见组合片段及其嵌套和多态性问题;为得到最小完备的测试路径,本文提出了EG的遍历策略和测试路径生成算法;最后,根据测试路径确定测试场景,并删除无效场景,生成测试用例.经实验验证,此方法可以基于UML顺序图与OCL约束进行系统地测试.     

Adaptive resource allocation for multicast orthogonal frequency division multiple access systems with guaranteed BER and rate

In this paper, we propose a resource allocation scheme to minimize transmit power for multicast orthogonal frequency division multiple access systems. The proposed scheme allows users to have different symbol error rate (SER) across subcarriers and guarantees an average bit error rate and transmission rate for all users. We first provide an algorithm to determine the optimal bits and target SER on subcarriers. Because the worst‐case complexity of the optimal algorithm is exponential, we further propose a suboptimal algorithm that separately assigns bit and adjusts SER with a lower complexity. Numerical results show that the proposed algorithm can effectively improve the performance of multicast orthogonal frequency division multiple access systems and that the performance of the suboptimal algorithm is close to that of the optimal one. Copyright © 2012 John Wiley & Sons, Ltd.     

MTNet: Design of a Wireless Test Framework for Heterogeneous Nanometer Systems-on-Chip

The rapid migration to nanometer design processes has brought an unprecedented level of integration by allowing system designers to pack a wide variety of functionalities on-chip, namely, systems-on-a-chip (SoCs). In the meantime, electronic testing becomes an enabling technology for this SoC paradigm, since the integration of various core tests is a big challenge, and has revealed a widening gap between design and manufacturing. In particular, the increasing complexity and density of nanometer SoCs have led to the problem of visibility and accessibility in testing. In this paper, we propose an integrated wireless test framework to resolve the acerbated core accessibility problem and to eliminate the incompatibility between the existing SoC test strategies and the next generation billion-transistor SoC specification. Under such a test strategy, the intra-chip wireless links form the wireless test access mechanism (TAM) to transport test data chip-wide. We present a self-configurable multi-hop wireless test micronetwork, dubbed MTNet, with simple and efficient data transmission protocols, and develop a system level design-for-testability structure. Consequently, we propose a geographic routing algorithm to find the test access paths for the deeply embedded cores and a path driven test scheduling algorithm to design and integrate the MTNet-based SoC test access architecture. Extensive simulation study show the feasibility and applicability of MTNet.     

一种基于状态的面向对象类测试策略

基于状态的类测试足面向对象测试技术的一个重要方面。一种新的基于状态的多角度的面向对象类测试策略,即融合UML Starecharts和EFSM这两个基于状态的模型,并引入Verification＆Validati。n思想。     

A formal approach to context scheduling for multicontextreconfigurable architectures

In this paper, we analyze the main issues in context scheduling for multicontext reconfigurable architectures from a formal point of view. We first provide an intuitive approach. which is later supported by a detailed analysis of the mathematical relations that express the reconfiguration process. This enables us to deduce a methodology for the minimization of context loading overhead, which considers the tradeoff between achievable system performance and algorithm efficiency. In this respect, the optimality necessary conditions are established in order to contrive an optimal search. However, as this approach is very time consuming we propose some heuristic techniques that reduce the algorithm complexity and accomplish very good results in relatively short execution time. This work has been developed as a part of an automated design environment for reconfigurable systems. A set of experiments has been developed so as to validate the theoretical results     

Strategy-based design of reusable business components

Grounded on principles of manufacturing design, component-based software development (CBSD) has been viewed as the future trend in software development. In this paper, we propose a methodology for component fabrication and argue that, as in classical product development, business strategy of component development companies must guide the design of reusable business components. Accordingly, we link business strategy with component design through managerial goals (identified as cost effectiveness, ease of assembly, customization, reusability, and maintainability). These managerial goals are then mapped to technical features (identified as coupling, cohesion, number of components, component size, and complexity). We develop a formal model, called Business Strategy-based Component Design that uses the object-oriented model of a business to derive the component structure by grouping appropriate object classes to achieve the desired business strategy. We examine the validity of the model by a two-phase application process.     

BPSK通信系统的部分最优MIMO检测算法

在BPSK调制下,基于最大似然（Maximum Likelihood,ML）准则的MIMO检测器是一个二进制二次规划问题,其计算复杂度随着天线数的增多呈指数增加,当天线数较多时,其计算量太大,无法满足实时通信的要求。本文提出了一种新的MIMO检测算法。使用新算法,可以在很小的计算开销下,求解出ML检测器的部分全局最优解,然后,将优先检测出的部分最优解从原二进制二次规划问题中剔除得到一个相对小规模问题,最后使用传统的次最优检测算法对该小规模问题进行求解。这样,新算法不仅可以得到比传统的次最优检测器更低的误码率,计算量又远小于ML最优检测器。本文的仿真结果验证了新算法的有效性。      

基于三元闭包理论的软件回归测试影响域分析方法

为提高测试充分性,减少系统维护的代价,提出了一种基于三元闭包理论的软件回归测试影响域分析方法。将软件系统抽象为一个社交网络,软件系统提供的功能抽象为虚拟人,为虚拟人之间定义交流通道类型,通过图论和三元闭包理论构建非直接发生联系的人的关系,给出回归建议。建立有向有权图模型,再结合三元闭包理论,利用算法计算每个测试项推荐系数,如果推荐系数大于0.5,则将该测试项纳入回归测试。该算法实现了测试用例集约简的同时,结合测试项社区网络针对性地将可能有缺陷的测试用例进行回归测试,满足网络频率规划管理软件等项目工程回归测试的应用需求,大大降低了人力成本,提高了回归测试效率。     

Optimal Joint Detection/Estimation in Fading Channels With Polynomial Complexity

The problem of sequence detection in frequency-nonselective/time-selective fading channels, when channel state information (CSI) is not available at the transmitter and receiver, is considered in this paper. The traditional belief is that exact maximum-likelihood sequence detection (MLSD) of an uncoded sequence over this channel has exponential complexity in the channel coherence time. Thus, for slowly varying channels, i.e., channels having coherence time on the order of the sequence length, the complexity appears to be exponential in the sequence length. In the first part of this work, it is shown that exact MLSD can be computed with only polynomial worst case complexity in the sequence length regardless of the operating signal-to-noise ratio (SNR) for equal-energy signal constellations. By establishing a relationship between the aforementioned complexity and the rank of the correlation matrix of the fading process, an understanding of how complexity of the optimal MLSD receiver varies as the channel dynamics change is provided. In the second part of this paper, the problem of decoding turbo-like codes in frequency-nonselective/time-selective fading channels without receiver CSI is examined. Using arguments similar to the ones used for the MLSD case, it is shown that the exact symbol-by-symbol soft-decision metrics (SbSSDMs) implied by the min-sum algorithm can be evaluated with polynomial worst case complexity in the sequence length regardless of SNR for equal-energy signal constellations. Finally, by simplifying some key steps in the polynomial-complexity algorithm, a family of fast, approximate algorithms is derived, which yield near-optimal performance     

New suboptimal multiuser detectors for synchronous CDMA systems

In code-division multiple access (CDMA) systems, the optimal multiuser detection is equivalent to an unconstrained quadratic bivalent optimization problem, and its computational complexity increases exponentially with the number of users. In this paper, we propose several new suboptimal detectors with a greatly reduced computational complexity based on a local minimization algorithm for a synchronous CDMA system. The performances of these detectors are compared with those of the conventional, optimal, and several other suboptimal detectors     

An automatic parameter extraction technique for advanced CMOS device modeling using genetic algorithm

We in this paper present an computational intelligence technique to extract semiconductor device model parameters. This solution methodology is based on a genetic algorithm (GA) with an exponential type weight function, renew operator, and adaptive sampling scheme. The proposed approach automatically extracts a set of complete parameters with respect to a specified compact model, such as a BSIM model for deep-submicron and nanoscale complementary metal-oxide-semiconductor (CMOS) devices. Compared with conventional artificial step-by-step fitting approaches, the proposed extraction methodology automatically tracks the shape variation of current-voltage (I-V) curves and examines the first derivative of I-V curves; therefore, highly accurate results can be obtained directly. Applying the renew operator will keep the evolutionary trend improving by removing the individuals without mainly features. The sampling strategy will speed up the evolution process and still maintain the extraction accuracy in a reasonable range. A developed prototype is successfully applied to extract model parameter of N- and P-metal-oxide-semiconductor field effect transistors (MOSFETs). This optimization method shows good physical accuracy and computational performance, and provides an alternative for optimal device modeling and circuit design in nanodevice era. Genetic algorithm based automatic model parameter extraction bridges the communities between circuit design and chip fabrication; in particular, it will significantly benefits design of system-on-a-chip.     

An application of univariate marginal distribution algorithm in MIMO communication systems

The paper discusses a sequence detector based on univariate marginal distribution algorithm (UMDA) that jointly estimates the symbols transmitted in a multiple input multiple output (MIMO) communication system. While an optimal maximum likelihood detection using an exhaustive search method is prohibitively complex, it has been shown that sphere decoder (SD) achieves the optimal bit error rate (BER) performance with polynomial time complexity for smaller array sizes. However, the worst‐case complexity of SD is exponential in the problem dimensions, this brings in question its practical implementation for larger number of spatial layers and for higher‐order signal constellation. The proposed detector shows promising results for this overly difficult and complicated operating environment, confirmed through simulation results. A performance comparison of the UMDA detector with SD is presented for higher‐order complex MIMO architectures with limited average transmit power. The proposed detector achieves substantial performance gain for higher‐order systems attaining a near optimal BER performance with reduced computational complexity as compared with SD. Copyright © 2009 John Wiley & Sons, Ltd.     

Test Scheduling for Network-on-Chip Using XY-Direction Connected Subgraph Partition and Multiple Test Clocks

It is attractive to reuse the on-chip functional interconnects as test access mechanism (TAM) in network-on-chip (NoC) system testing. However, in the methodology of NoC-reuse as TAM, the influence factors in NoC testing significantly increased. To further reduce test time and show significant gains over other work, we propose XY-direction connected subgraph partition (XYCSP) approach to eliminate the path conflicts before testing, and concurrently determine the position of test access points. We then present a multiple test clock strategy to bridge the gap between the NoC channel bandwidth and the core test wrapper bandwidth. With the help of adaptive probability gate quantum-inspired evolutionary algorithm (APGQEA) strategy, which blends adaptive strategy and multi-nary oriented techniques, the proposed NoC test scheduling algorithm permits quick exploration and exploitation of the solution space. Moreover, power constraints are also taken into account. Experimental results for the ITC’02 benchmarks show that the proposed scheme can achieve shorter test time compared to prior works.     

Predictive subset testing: optimizing IC parametric performancetesting for quality, cost, and yield

A formal methodology for IC parametric performance testing, called predictive subset testing, is presented. It is based on a statistical model of parametric process variation. In this Monte-Carlo-based approach, a statistical process simulation is used together with circuit simulation to determine the joint probability distribution of a set of circuit performances. By evaluating the joint probability distribution, rather than assuming the performances to be independent, correlations that exist between them are used to reduce the number of performances that need to be explicitly tested. Once a subset of performances for explicit testing has been identified, regression models are constructed for the untested performances, and from the confidence intervals test limits are assigned for the tested performances. In this manner, the values of the untested performances within desired quality levels are predicted, reducing test complexity and cost     

Knowledge-Based Artificial Neural Network Models for Microstrip Radial Stubs

Radial stubs are a superior choice over low characteristic impedance rectangular stubs in terms of providing an accurate localized zero-impedance reference point and maintaining a low input impedance value over a wide frequency range. In this paper, knowledge-based artificial neural networks are used to model the microstrip radial stubs. Using space-mapping technology and Huber optimization make the neural network models for radial stubs decrease the number of training data, improve generalization ability, and reduce the complexity of the neural network topology with respect to the classical neuromodeling approach. The neural networks are developed for design and optimization of radial stubs, which are robust both from the angle of time of computation and accuracy.     

Design of irregular LDPC codes with optimized performance-complexity tradeoff

The optimal performance-complexity tradeoff for error-correcting codes at rates strictly below the Shannon limit is a central question in coding theory. This paper proposes a numerical approach for the minimization of decoding complexity for long-block-length irregular low-density parity-check (LDPC) codes. The proposed design methodology is applicable to any binary-input memoryless symmetric channel and any iterative message-passing decoding algorithm with a parallelupdate schedule. A key feature of the proposed optimization method is a new complexity measure that incorporates both the number of operations required to carry out a single decoding iteration and the number of iterations required for convergence. This paper shows that the proposed complexity measure can be accurately estimated from a density-evolution and extrinsicinformation transfer chart analysis of the code. A sufficient condition is presented for convexity of the complexity measure in the variable edge-degree distribution; when it is not satisfied, numerical experiments nevertheless suggest that the local minimum is unique. The results presented herein show that when the decoding complexity is constrained, the complexity-optimized codes significantly outperform threshold-optimized codes at long block lengths, within the ensemble of irregular codes.     

基于遗传算法的低轨天基雷达星座设计

从目标监视性能的角度出发,分析了低轨天基雷达星座的卫星总数、能量需求以及星座发射费用等优化目标。综合考虑了Walker星座的碰撞等约束问题,建立了低轨天基雷达星座设计的优化目标。提出了一种基于遗传算法的低轨天基雷达星座设计方法。根据天基雷达星座的特点,该算法在进化过程中使用了非可行解修正和约束分级等约束处理方法,有效提高了算法的运算效率。通过仿真实验验证了该方法能够有效的同时优化低轨天基雷达星座的构形和卫星参数。     

Fano Multiple-Symbol Differential Detectors for Differential Unitary Space–Time Modulation

We present a class of suboptimal multiple-symbol differential detectors (MSDDs) for differential unitary space-time (ST) codes in a time-selective Rayleigh flat-fading channel. These noncoherent detectors, termed Fano ST-MSDDs, employ the well-known Fano algorithm as their decoding engines. Their bit-error rate (BER) performance is excellent, as there is no irreducible error floor, even at very high fade rates. Compared with the sphere decoder, which is optimal, our best detector, termed an on-demand bi-Fano ST-MSDD, suffers only a 0.3 dB degradation in power efficiency. However, its computational complexity, as a function of the signal-to-noise ratio (SNR), is consistently lower than that of the sphere decoder and does not experience the exponential growth in complexity in the latter when the SNR decreases. It can thus be concluded that the Fano algorithm is a powerful detection strategy for differential ST codes in fading channels. Our main contribution is in making the modifications and improvements to the Fano algorithm that enables this realization. The innovations include the bi-Fano, edge-bi-Fano, and on-demand bi-Fano search strategies, as well as a new dynamic threshold adjustment scheme for avoiding unnecessary back-and-forth node evaluations during backtracking     

An improvement to the interacting multiple model (IMM) algorithm

Computing the optimal conditional mean state estimate for a jump Markov linear system requires exponential complexity, and hence, practical filtering algorithms are necessarily suboptimal. In the target tracking literature, suboptimal multiple-model filtering algorithms, such as the interacting multiple model (IMM) method and generalized pseudo-Bayesian (GPB) schemes, are widely used for state estimation of such systems. We derive a reweighted interacting multiple model algorithm. Although the IMM algorithm is an approximation of the conditional mean state estimator, our algorithm is a recursive implementation of a maximum a posteriori (MAP) state sequence estimator. This MAP estimator is an instance of a previous version of the EM algorithm known as the alternating expectation conditional maximization (AECM) algorithm. Computer simulations indicate that the proposed reweighted IMM algorithm is a competitive alternative to the popular IMM algorithm and GPB methods     

Optimal Defense Strategy Against Intentional Attacks

This paper presents a generalized model of damage caused to a complex multi-state series-parallel system by intentional attack. The model takes into account the defense strategy that presumes separation and protection of system elements. The defense strategy optimization methodology is suggested, based on the assumption that the attacker tries to maximize the expected damage of an attack. An optimization algorithm is presented that uses a universal generating function technique for evaluating the losses caused by system performance reduction, and a genetic algorithm for determining the optimal defense strategy. Illustrative examples of defense strategy optimization are presented