需求变更影响分析模型及相关技术研究

需求是后续开发活动的基准，早期的一些研究者认为应该在需求完全确定之后再进行后续开发，Royce所提出的瀑布模型就是这种思想的一个体现。但是，实践经验告诉我们，不管前期的需求分析做的多么完美，需求还是会发生变更。一方面是因为需求本身很复杂，对它的分析、理解和描述是一个循序渐进的过程，不可能一蹴而就；另一方面由于用户期望和偏好的改变、市场环境的转变、使用环境的日益复杂、技术的革新等都会使得原有的软件系统无法满足各涉众的利益。因此，需求变更是软件开发中固有的规律，是不可避免和普遍存在的。 需求变更通常会导致需求间及需求与后续工作产品间的不一致。因此，频繁的需求变更会造成产品质量下降、进度延期、成本超支等问题。变更影响分析(Change Impact Analysis)通过分析变更对象及其相关工作产品间的关系来评估变更造成的影响，从而控制变更。现有方法多数是从软件维护的角度，对代码的变更影响进行分析，过于细节和技术化，不能对需求变更影响分析提供有力支持。即使针对需求变更的影响分析方法也只是基于形式化需求规约，通过分析需求间的关系来识别影响范围，并未考虑需求变更对后续工作产品造成的影响，同时形式化需求规约的应用困难也限制了该方法的实用性。此外，随着需求和工作产品的规模与复杂性日益增加，使得手工建立和维护需求间及需求与工作产品间关系面临着不小的难度。 基于以上分析，本文提出了针对自然语言需求规约的需求变更影响分析模型RCIAM (Requirement Change Impact Analysis Model)，围绕着如何自动识别和筛选需求间的关系——横向需求跟踪关系(Horizontal Requirement Traceability)、如何自动识别和筛选需求与工作产品间的关系——纵向需求跟踪关系(Vertical Requirement Traceability)、如何较全面的进行需求变更影响计算和决策三个问题展开了研究。 本文的主要贡献有： (1) 提出了需求变更影响分析模型RCIAM 本文对RCIAM进行了形式化定义。该模型不但提供了需求变更影响分析算法和对决策的支持，还提供了自动识别横向和纵向需求跟踪关系的方法。RCIAM主要包含数据处理和数据分析两个层次。数据处理层采用了文本处理(Text Processing)技术实现了横向和纵向需求跟踪关系的自动识别，为数据分析层提供需求跟踪关系数据；数据分析层基于需求跟踪关系数据，在产生需求变更申请(Change Request)时，进行量化影响计算，并提供决策支持。 (2) 提出了横向需求跟踪关系的识别与筛选方法 在对自然语言需求规约文档进行深入分析后，我们发现了两种与需求变更影响密切相关的关系类型，并从文本相似性的角度将它们定义为相似跟踪关系和引用跟踪关系。在将需求项拆分为需求片段的基础上，利用信息检索技术(Information Retrieval，IR)计算需求片段间的文本相似度，并设计了相应的算法对相似跟踪关系和引用跟踪关系进行自动识别。最后，提出了“变更影响跟踪”的规则来辅助对候选跟踪关系的人工筛选。 (3) 提出了纵向需求跟踪关系的识别与筛选方法 已有的研究多采用IR技术来自动建立需求与工作产品之间的跟踪关系，但是却存在着精度不理想的问题。我们从查全率(Recall)和查准率(Precision)的角度，分析了应用IR技术自动建立需求与代码跟踪关系的方法中产生的错误关系，发现了造成精度问题的根源所在。依据这一发现，基于现有方法，本文方法加入了相关反馈(Relvant Feedback)辅助识别和代码注释信息辅助识别等改进措施，并提供了人工筛选策略。 (4) 提出了需求变更影响分析计算与决策方法 本文通过矩阵运算说明了需求变更影响通过需求跟踪关系传播到其它需求和工作产品的过程，并设计了相应的需求变更影响分析算法。该算法考虑变更发生在不同阶段时对不同类型工作产品的影响，采用变更类型和关系强度两个因子加权计算影响值，并提出了根据影响值来进行变更决策的方法。 (5) 应用研究 结合中科方德公司Qone平台的开发，对以上工作进行了应用研究和性能分析。在Qone平台的需求管理工具版本1.0的开发中，首先采用本文方法对横向和纵向需求跟踪关系进行了自动识别，然后对开发期间发生的十次需求变更申请进行了影响分析和决策。在项目完成后，设计了实验对横向和纵向需求跟踪关系的识别进行了性能分析。结果表明，本文方法能够有效辅助进行需求变更影响分析。

Iterative method using consistent mass matrix in axisymmetrical finite element analysis of hypervelocity impact

We present in this paper an iterative method using consistent mass matrix in axisymmetrical finite element analysis of hypervelocity impact. To retain the advantage of integration on an element-by-element basis which is at the heart of modern hydrocodes, we suggest that the first step should be to solve for accelerations at an advanced time step by using the lumped mass approach, then iterate using a consistent mass matrix to improve the estimate. Examples are given to show the improved resolution with the new method.

The application of B-P constitutive equations in finite element analysis of high velocity impact

We present in this paper the application of B-P constitutive equations in finite element analysis of high velocity impact. The impact process carries out in so quick time that the heat-conducting can be neglected and meanwhile, the functions of temperature in equations need to be replaced by functions of plastic work. The material constants in the revised equations can be determined by comparison of the one-dimensional calculations with the experiments of Hopkinson bar. It can be seen from the comparison of the calculation with the experiment of a tungsten alloy projectile impacting a three-layer plate that the B-P constitutive equations in that the functions of temperature were replaced by the functions of plastic work can be used to analysis of high velocity impact.

The impact of chromosome sorting and painting on the comparative analysis of primate genomes

Chromosome sorting by flow cytometry is the main source of chromosome-specific DNA for the production of painting probes. These probes have been used for cross-species in situ hybridization in the construction of comparative maps, in the study of karyotype evolution and phylogenetics, in delineating territories in interphase nuclei, and in the analysis of chromosome breakpoints. We review here the contributions that this technology has made to the analysis of primate genomes. Copyright (C) 2005 S. Karger AG, Basel.

Analysis of arable land loss and its impact on rural sustainability in Southern Jiangsu Province of China

Rapid urbanization and industrialization in southern Jiangsu Province have consumed a huge amount of arable land. Through comparative analysis of land cover maps derived from TM images in 1990, 2000 and 2006, we identified the trend of arable land loss. It is found that most arable land is lost to urbanization and rural settlements development. Urban settlements, rural settlements, and industrial park-mine-transport land increased, respectively, by 87 997 ha (174.65%), 81 041 ha (104.52%), and 12 692 ha (397.99%) from 1990 to 2006. Most of the source (e.g., change from) land covers are rice paddy fields and dryland. These two covers contributed to newly urbanized areas by 37.12% and 73.52% during 1990-2000, and 46.39% and 38.86% during 2000-2006. However, the loss of arable land is weakly correlated with ecological service value, per capita net income of farmers, but positively with grain yield for some counties. Most areas in the study site have a low arable land depletion rate and a high potential for sustainable development. More attention should be directed at those counties that have a high depletion rate but a low potential for sustainable development. Rural settlements should be controlled and rationalized through legislative measures to achieve harmonious development between urban and rural areas, and sustainable development for rural areas with a minimal impact on the ecoenvironment. (C) 2009 Elsevier Ltd. All rights reserved.

Analysis of the sea-level variability along the Chinese coast and estimation of the impact of a CO2-perturbed atmospheric circulation

The relationship between monthly sea-level data measured at stations located along the Chinese coast and concurrent large-scale atmospheric forcing in the period 1960-1990 is examined. It is found that sea-level varies quite coherently along the whole coast, despite the geographical extension of the station set. A canonical correlation analysis between sea-level and sea-level pressure (SLP) indicates that a great part of the sea-level variability can be explained by the action of the wind stress on the ocean surface. The relationship between sea-level and sea-level pressure is analyzed separately for the summer and winter half-years. In winter, one factor affecting sea-level variability at all stations is the SLP contrast between the continent and the Pacific Ocean, hence the intensity of the winter Monsoon circulation. Another factor that affects coherently all stations is the intensity of the zonal circulation at mid-latitudes. In the summer half year, on the other hand, the influence of SLP on sea-level is spatially less coherent: the stations in the Yellow Sea are affected by a more localized circulation anomaly pattern, whereas the rest of the stations is more directly connected to the intensity of the zonal circulation. Based on this analysis, statistical models (different for summer and winter) to hindcast coastal sealevel anomalies from the large-scale SLP field are formulated. These models have been tested by fitting their internal parameters in a test period and reproducing reasonably the sea-level evolution in an independent period. These statistical models are also used to estimate the contribution of the changes of the atmospheric circulation on sea-level along the Chinese coast in an altered climate. For this purpose the ouput of 150 year-long experiment with the coupled ocean-atmosphere model ECHAM1-LSG has been analyzed, in which the atmospheric concentration of greenhouse gases was continuously increased from 1940 until 2090, according to the Scenario A projection of the Intergovermental Panel on Climate Change. In this experiment the meridional (zonal) circulation relevant for sea-level tends to become weaker (stronger) in the winter half year and stronger (weaker) in summer. The estimated contribution of this atmospheric circulation changes to coastal sea-level is of the order of a few centimeters at the end of the integration, being in winter negative in the Yellow Sea and positive in the China Sea with opposite signs in the summer half-year.