面向对象系统的类之间依赖关系度量研究

类之间的依赖关系,对于面向对象系统分析、设计和测试都有重要的意义。本文首先对类之间的依赖关系进行了定义和说明,并细分其为数据依赖和方法依赖,在此基础上。提出依赖度和被依赖度两种度量方法,并进行了严格的语义分析和说明。     

软件设计中的模块依赖研究

针对软件开发中的模块依赖提出了一种新的模块间依赖模型.新模型的关键思想是依赖是由规范调节的,这样不仅记录了依赖的存在,而且记录了依赖的质量.单个模块不一定只提供单个规范,每个依赖模块可以通过不同的规范使用它.这种依赖的概念比传统的概念更容易解释一些常见的编程习惯用法,并为分析和设计提供了新的评价体系.     

对象类之间依赖关系度量分析

类之间的依赖关系,对于面向对象系统分析、设计和测试都有重要的意义。该文首先对类之间的依赖关系进行了定义和说明,并细分其为数据依赖和方法依赖,在此基础上,提出依赖度和被依赖度两种度量方法,并进行了严格的语义分析和说明。最后,文章提出依据这两种度量方法来确定类的规模大小的算法。     

一种基于逻辑的Java模块依赖图构建工具

目前Java模块依赖图MDG(Module Dependency Graph)的构建工具还比较稀缺,从一定程度上限制了基于MDG图的软件模块聚类算法的应用。针对这一问题,提出一种基于逻辑的Java模块依赖图构建工具TL4JMDG(the tool logic-based for Java MDG)。在开源框架JTransformer和tu Prolog的支持下,TL4JMDG工具以逻辑方式实现了Java模块关系的抽取和MDG图的生成。阐述TL4JMDG工具的设计与实现,并给出TL4JMDG工具和基于Chava工具构建MDG的耗时比较。TL4JMDG工具具有较好的可配置性、可扩展性和性能,使得目前已有的基于MDG图的聚类算法能更好地应用于Java软件模块聚类。     

时态实体依赖关系与度量方法研究

实体间存在各种各样的依赖关系,尤其是在软件开发过程中,软件实体间的依赖关系对软件的变更影响分析以及风险分析等都具有重大影响。依赖图作为最常用的依赖关系表示方法,其节点与边的定义与属性计算不尽相同,且大部分方法中并没有考虑到节点与边的时态属性。针对时态实体依赖图,文中系统地提出了时态实体依赖关系的形式化定义并分析了其特性,然后分析了时态实体依赖图的节点中心性、节点重要性、节点依赖度和边的重要性等4个度量指标,同时,针对MAVEN数据集分析了上述各个指标随时间变化的规律。     

一个概率关系专家数据库模型

该文在关系数据库理论的基础上,针对元组级不确定信息,给出了一种概率知识表示的方法,并以此为基础,首先推广传统关系到概率关系,进而推广关系代数到概率关系代数,建立了一个简单的概率关系数据模型,并给出了该模型的一些基本操作,如选择、投影,笛卡尔积、并、差等。该模型对存储和管理不确定信息的数据库的建立有一定参考价值。     

IRP用户视图间依赖关系的度量

用户视图间的依赖关系对于信息资源规划中的数据分析和数据建模有着重要的意义。该文对用户视图间的依赖关系进行了定义和说明,并细分其为数据依赖和操作依赖,在此基础上,对用户视图间的依赖关系进行了度量,提出了依赖度和被依赖度2种度量方法,为规范用户视图提供了依据。     

基于内存依赖关系度量的解密数据提取方法

基于数据流的程序分析算法能够有效识别程序的数据处理流程,但是对于采用数据加密技术进行通信的网络程序,数据流分析由于无法准确识别、提取解密数据而失效.针对如何提取解密数据,提出一种基于内存依赖度的算法,从解密数据内存依赖度的角度研究如何提取加密通信中的明文数据及实现该算法的原型工具EncMemCheck.通过实验对比分析该算法的优缺点,并在加密通信软件UnrealIrcd上进行实际测试,验证了算法的准确性和实用性.     

一种需求变更影响的评估算法

通过对需求依赖关系的分析与归纳,给出了需求依赖关系的依赖形式;采用回溯法来搜索和界定需求变更的影响范围,给出了变更影响的量化方法;从需求依赖关系的视角,设计了一个可以量化评估需求变更影响的算法。通过一个“样例学习”的例子,展现了该评估算法的稳定性。     

基于依赖关系图和通用漏洞评分系统的网络安全度量

管理人员通常使用一些网络安全指标作为度量网络安全的重要依据。通用漏洞评分系统（CVSS）是目前人们普遍认同的网络度量方式之一。针对现有的基于CVSS的网络安全度量无法精确测量网络受到攻击的概率和影响两方面得分的问题，提出一种基于依赖关系图和CVSS的改进基础度量算法。首先发掘攻击图中漏洞节点的依赖关系，构建依赖关系图；然后根据依赖关系修改CVSS中漏洞的基础度量算法；最后聚合整个攻击图中的漏洞得分，得到网络受到攻击的概率及影响两方面的得分。采用模拟攻击者进行仿真实验，结果表明，该算法在算法精确度和可信度方面明显优于汇总CVSS分数算法，更加接近实际仿真结果。     

Adaptive probability analysis using an enhanced hybrid mean value method

This paper proposes an adaptive probability analysis method that can effectively generate the probability distribution of the output performance function by identifying the propagation of input uncertainty to output uncertainty. The method is based on an enhanced hybrid mean value (HMV+) analysis in the performance measure approach (PMA) for numerical stability and efficiency in search of the most probable point (MPP). The HMV+ method improves numerical stability and efficiency especially for highly nonlinear output performance functions by providing steady convergent behavior in the MPP search. The proposed adaptive probability analysis method approximates the MPP locus, and then adaptively refines this locus using an a posteriori error estimator. Using the fact that probability levels can be easily set a priori in PMA, the MPP locus is approximated using the interpolated moving least-squares method. For refinement of the approximated MPP locus, additional probability levels are adaptively determined through an a posteriori error estimator. The adaptive probability analysis method will determine the minimum number of necessary probability levels, while ensuring accuracy of the approximated MPP locus. Several examples are used to show the effectiveness of the proposed adaptive probability analysis method using the enhanced HMV+ method.     

Entrenchment versus Dependence: Coherence and Foundations in Belief Change

We describe the relation between coherence and foundations approaches to belief change in terms of a correspondence between epistemic entrenchment relations(Gärdenfors and Makinson, 1988; Rott, 1992) and dependence consequence relations from Bochman (1999, 2000a).The general conclusion of the study is that dependence consequence relations are sufficiently expressive to subsume the notion of an epistemic entrenchment and its generalizations.     

目视检测损伤检出概率BP神经网络预测模型

为了获得更可靠的检出概率,提高目视检测结果准确性,保证航空维修安全,根据检测环境影响因素实验结果,选取照明条件、检测距离、检测角度、损伤深度作为检测结果影响因素,采用反向传播（ BP）神经网络,以4个影响因素作为输入层神经元,检出概率作为输出层神经元,通过网络训练对样本数据进行仿真,建立检出概率预测模型,通过比较预测和实验数据对模型进行检验。结果表明,模型预测与实验所得检出概率值均方百分比误差为4.79',模型预测结果是有效可行的。根据目视检测损伤检出概率BP神经网络预测模型可以选择符合要求的检测条件。     

Using local transition probability models in Markov random fields for forest change detection

Change detection based on the comparison of independently classified images (i.e. post-classification comparison) is well-known to be negatively affected by classification errors of individual maps. Incorporating spatial-temporal contextual information in the classification helps to reduce the classification errors, thus improving change detection results. In this paper, spatial-temporal Markov Random Fields (MRF) models were used to integrate spatial-temporal information with spectral information for multi-temporal classification in an attempt to mitigate the impacts of classification errors on change detection. One important component in spatial-temporal MRF models is the specification of transition probabilities. Traditionally, a global transition probability model is used that assumes spatial stationarity of transition probabilities across an image scene, which may be invalid if areas have varying transition probabilities. By relaxing the stationarity assumption, we developed two local transition probability models to make the transition model locally adaptive to spatially varying transition probabilities. The first model called locally adjusted global transition model adapts to the local variation by multiplying a pixel-wise probability of change with the global transition model. The second model called pixel-wise transition model was developed as a fully local model based on the estimation of the pixel-wise joint probabilities. When applied to the forest change detection in Paraguay, the two local models showed significant improvements in the accuracy of identifying the change from forest to non-forest compared with traditional models. This indicates that the local transition probability models can present temporal information more accurately in change detection algorithms based on spatial-temporal classification of multi-temporal images. The comparison between the two local transition models showed that the fully local model better captured the spatial heterogeneity of the transition probabilities and achieved more stable and consistent results over different regions of a large image scene.     

具有模型概率修正的新颖IMMPDA算法

为了有效提高杂波环境中机动目标跟踪的精度,将标量交互式多模型(SIMM)算法与概率数据关联(PDA)算法结合成SIMMPDA算法.其中,PDA算法能够有效处理杂波环境下的数据关联与测量不确定性.SIMM算法处理运动模型间的切换,且在线性最小方差意义下获得目标的最优状态估计.而考虑因杂波的干扰导致各时刻的匹配模型占优程度不明显的问题,故再对各时刻SIMMPDA算法所得的后验模型概率进行修改,得到一个基于模型概率修改的SIMMPDA算法,即为M-SIMMPDA算法.仿真结果表明,所提算法的跟踪精度得到一定程度的提高.     

D2D缓存网络中基于随机几何的成功卸载概率分析

针对所有移动用户均具有缓存能力的终端直传（D2D）缓存网络，将移动用户的位置分布建模为均匀泊松点过程（HPPP），并在此基础上结合内容缓存和内容请求的随机性，对网络干扰进行了精确分析和特定场景下的近似分析。考虑到D2D缓存技术融合了用户终端缓存与D2D通信的双重特点，即内容卸载包括自卸载和D2D卸载两种卸载方式、内容传输需要满足接收端信干比（SIR）和D2D距离的双重约束，利用随机几何理论推导出D2D缓存网络的成功卸载概率（SOP）的闭式表达式。仿真结果表明，结合D2D缓存网络特点的SOP更具有一般性，在特定场景下可以退化成已有研究中的特例。例如，在用户密集分布以及D2D最大通信距离较大的情况下SOP会退化成不考虑D2D距离约束的成功传输概率（STP）。     

基于依赖性分析的回归测试用例选择

在面向对象程序功能性测试中,扩展有限状态自动机(ESFM)是一种有效的建模表示方式。本文主要探讨面向对象程序回归测试中的用例选择技术,对程序对应的EFSM模型进行数据依赖和控制依赖分析,确定程序中修改部分的波及影响,再进行测试用例的选择。     

Error probability analysis of an MC-DS-CDMA system under Weibull fading with a moment-generating function

The performance, with error probability analysis, of an MC-DS-CDMA (multi-carrier direct-sequence coded-division multiple-access) system adopting a Weibull fading channel is proposed and evaluated. On the basis of the multivariate MGF (moment-generating function) of Weibull statistics and an alternative expression of the Q-function, an approximate BER (bit-error rate) expression is derived for an MC-DS-CDMA system combined with MRC (maximal ratio-combining) diversity. The Weibull fading model is applied to analyze the BER performance of an MC-DS-CDMA system by considering multi-users with both multi-carriers and the phenomena of PBI (partial-band interference) cases. Regardless of the channel model assumed or the user number considered, it is noteworthy that the PBI is definitely the most important factor dominating the performance of an MC-DS-CDMA system, according to the results obtained in this study. The reliability of the proposed schemes can be explicitly verified in accordance with the previously reported results. Thus, we assert that the aim of the performance analysis of an MC-DS-CDMA system operating under Weibull fading has been completely achieved.     

Imprecise probability trees: Bridging two theories of imprecise probability

We give an overview of two approaches to probability theory where lower and upper probabilities, rather than probabilities, are used: Walley's behavioural theory of imprecise probabilities, and Shafer and Vovk's game-theoretic account of probability. We show that the two theories are more closely related than would be suspected at first sight, and we establish a correspondence between them that (i) has an interesting interpretation, and (ii) allows us to freely import results from one theory into the other. Our approach leads to an account of probability trees and random processes in the framework of Walley's theory. We indicate how our results can be used to reduce the computational complexity of dealing with imprecision in probability trees, and we prove an interesting and quite general version of the weak law of large numbers.     

基于最佳选择的星地协作系统中断概率

针对卫星信道的衰落特性和阴影效应,分析了一种星地协作系统(HSTCS),并通过对陆地卫星移动通信(LMS)信道进行分析得到其中断概率的闭环表达方法.在源节点(卫星)到目的节点(地面终端)间采用解码前传(DF)模式,目的节点将来自卫星和信噪比最大的中继节点的信号进行合并,并通过Matlab进行仿真.仿真结果表明,同直接传输相比,该系统能够通过获得分集增益,有效提高系统中断性能.