基于UML的COSMIC-FFP度量方法

针对目前的软件规模度量方法中存在的主观性强、可重复性差的问题,通过将UML引入到度量过程中来改善当前的软件度量方法。分析UML主要部件(用例图、类图和时序图)的语义和COSMIC-FFP的主要元素(功能用户、层、边界、数据组和功能过程),建立其间的对应关系,给出15条映射规则,同时还提出基于UML的COSMIC-FFP度量步骤。实例结果证明,该方法能客观有效地度量软件功能规模。     

基于UML的软件度量

针对现有软件度量估算困难、精确度不高的问题,在预测性对象点基础上改进并提出基于UML的软件度量方法,可以从用例、序列图、类图度量软件。结果证明,与预测性对象点相比,该方法的精度提高了5%左右,其子系统偏差方向一致。     

基于UML技术的功能点度量研究与应用

准确的规模度量在做好软件成本估算的过程中有着举足轻重的作用,功能点规模度量分析在业界被应用广泛,但考虑到功能点被分解时随意性较大,而UML是面向对象程序设计方法中进行分析和设计的标准建模语言,于是文章提供了一种使用UML技术中的用例图及用例描述和类图相结合的方法对应用系统进行功能点分析,使得开发者能使用该方法能在开发的早期估算出系统的规模,并将此方法应用于企业信息化协同办公自动化系统中。     

基于UML的仓储管理系统的分析设计

统一建模语言(UML)是面向对象分析和设计过程中重要的建模工具,适用于软件生命周期的各个阶段.以仓储管理系统为例,采用面向对象的方法,介绍UML的建模机制;叙述了仓储管理系统的用例建模、动态建模的过程,详细描述了基于UML该系统的用例图、活动图、顺序图、协作图.     

基于领域工程的社区信息化系统构件开发方法研究

针对当前社区信息化系统的可重构性较差、资源不能有效共享、重复开发等不足,引入了领域工程的方法,结合软件复用的思想,按照领域工程的开发步骤,通过对社区智能供暖子领域的分析,利用UML建模工具得到了该领域的用例图、类图和顺序图,介绍了领域工程与社区信息化系统相结合的方法技巧,最后得出了基于领域工程的社区智能供暖子领域的各项功能构件,为实现软件的工业化生产铺平了道路.     

基于UML的精品课程远程教育网站模型设计

UML是面向对象的统一建模语言,所设计的软件模型具有可重用性的特点。使用UML新方法开发精品课程网站,用UML用例图做需求分析,用UML类图和顺序图进行系统静态和动态设计,最终用PHP程序语言和MYSQL数据库来实现网站软件。经UML建模后的精品课程远程教育网站模型可以多次应用,从而提高网站软件的开发效率。     

一种基于UML建模的实时测控系统设计

为了实现软件产品工程化、标准化的目标,在实时测控软件的开发过程中需要引入现代软件工程思想和方法来规范开发流程、保证软件质量.由于实时测控软件特殊应用领域,实时测控软件通常采用模块化设计方法和多层次体系结构.在软件建模方面,UML建模方法也被用于对实时测控软件进行建模.在实时测控系统软件的开发过程中,本文采用了多层次的体系结构,并分别采用UML用例图、类图和顺序图对软件的功能、结构和信息活动进行建模,最终完成软件系统的构建.     

基于UML的图书馆管理系统的分析与设计

利用 Rational Rose对图书馆管理系统进行UML建模,建立了系统类图,用户用例图,用户顺序图和系统活动图等.通过对图书馆管理系统的实例建模,详细地阐述了基于UML的建模过程.     

功能点估算法在彩票行业的应用

本文主要介绍了基于NESMA功能点估算法的软件成本度量,及其在彩票行业软件项目中的应用。软件的规模大小在项目的早期计划与实践过程中具有指导作用,NESMA功能点法是一种基于用户需求并且独立于开发语言的估算方法,能够比较准确地度量规模。本文首先阐述了应用NESMA功能点法估算软件规模的详细方法和步骤,并结合彩票行业软件开发的实际情况,以及参考软件行业基准数据,对其在彩票软件开发成本估算中的实际应用进行了总结,并以实例说明该方法在彩票行业的适用性和局限性。     

UML在设备大小修文件包系统需求分析中的应用

系统需求分析是软件生命周期中最重要的一个阶段。本文介绍了采用UML在需求分析阶段的建模步骤,并以设备大小修文件包系统为例,使用用例图和顺序图论述了具体建模过程。     

Towards a simplified definition of Function Points

BackgroundThe measurement of Function Points is based on Base Functional Components. The process of identifying and weighting Base Functional Components is hardly automatable, due to the informality of both the Function Point method and the requirements documents being measured. So, Function Point measurement generally requires a lengthy and costly process.ObjectivesWe investigate whether it is possible to take into account only subsets of Base Functional Components so as to obtain functional size measures that simplify Function Points with the same effort estimation accuracy as the original Function Points measure. Simplifying the definition of Function Points would imply a reduction of measurement costs and may help spread the adoption of this type of measurement practices. Specifically, we empirically investigate the following issues: whether available data provide evidence that simplified software functionality measures can be defined in a way that is consistent with Function Point Analysis; whether simplified functional size measures by themselves can be used without any appreciable loss in software development effort prediction accuracy; whether simplified functional size measures can be used as software development effort predictors in models that also use other software requirements measures.MethodWe analyze the relationships between Function Points and their Base Functional Components. We also analyze the relationships between Base Functional Components and development effort. Finally, we built effort prediction models that contain both the simplified functional measures and additional requirements measures.ResultsSignificant statistical models correlate Function Points with Base Functional Components. Basic Functional Components can be used to build models of effort that are equivalent, in terms of accuracy, to those based on Function Points. Finally, simplified Function Points measures can be used as software development effort predictors in models that also use other requirements measures.ConclusionThe definition and measurement processes of Function Points can be dramatically simplified by taking into account a subset of the Base Functional Components used in the original definition of the measure, thus allowing for substantial savings in measurement effort, without sacrificing the accuracy of software development effort estimates.     

An evaluation of the statistical convertibility of Function Points into COSMIC Function Points

Since the introduction of COSMIC Function Points, the problem of converting historical data measured using traditional Function Points into COSMIC measures have arisen. To this end, several researchers have investigated the possibility of identifying the relationship between the two measures by means of statistical methods. This paper aims at improving statistical convertibility of Function Points into COSMIC Function Points by improving previous work with respect to aspects—like outlier identification and exclusion, model non-linearity, applicability conditions, etc.—which up to now were not adequately considered, with the purpose of confirming, correcting or enhancing current models. Available datasets including software sizes measured both in Function Points and COSMIC Function Points were analyzed. The role of outliers was studied; non linear models and piecewise linear models were derived, in addition to linear models. Models based on transactions only were also derived. Confidence intervals were used throughout the paper to assess the values of the models’ parameters. The dependence of the ratio between Function Points and COSMIC Function Points on size was studied. The union of all the available datasets was also studied, to overcome problems due to the relatively small size of datasets. It is shown that outliers do affect the linear models, typically increasing the slope of the regression lines; however, this happens mostly in small datasets: in the union of the available datasets there is no outlier that can influence the model. Conditions for the applicability of the statistical conversion are identified, in terms of relationships that must hold among the basic functional components of Function Point measures. Non-linear models are shown to represent well the relationships between the two measures, since the ratio between COSMIC Function Points and Function Points appears to increase with size. In general, it is confirmed that convertibility can be modeled by different types of models. This is a problem for practitioners, who have to choose one of these models. Anyway, a few practical suggestions can be derived from the results reported here. The model assuming that one FP is equal to one CFP causes the biggest conversion errors observed and is not generally supported. All the considered datasets are characterized by a ratio of transaction to data functions that is fairly constant throughout each dataset: this can be regarded as a condition for the applicability of current models; under this condition non-linear (log–log) models perform reasonably well. The fact that in Function Point Analysis the size of a process is limited, while it is not so in the COSMIC method, seems to be the cause of non linearity of the relationship between the two measures. In general, it appears that the conversion can be successfully based on transaction functions alone, without losing in precision.     

Reasoning about UML/OCL class diagrams using constraint logic programming and formula

Model Driven Engineering promotes the use of models as the main artifacts in software and system development. Verification and validation of models are key activities to ensure the quality of the system under development. This paper presents a framework to reason about the satisfiability of class models described using the Unified Modeling Language (UML). The proposed framework allows us to identify possible design flaws as early as possible in the software development cycle. More specifically, we focus on UML Class Diagrams annotated with Object Constraint Language (OCL) invariants, which are considered to be the main artifacts in Object-Oriented analysis and design for representing the static structure of a system. We use the Constraint Logic programming (CLP) paradigm to reason about UML Class Diagrams modeling foundations. In particular, we use Formula as a model-finding and design space exploration tool. We also present an experimental Eclipse plug-in, which implements our UML model to Formula translation proposal following a Model Driven Architecture (MDA) approach. The proposed framework can be used to reason, validate, and verify UML Class Diagram software designs by checking correctness properties and generating model instances using the model exploration tool Formula.     

UML类图中面向非功能属性的描述和检验

为系统构建模型是软件开发中的一项关键活动.一个高质量的模型不仅要包含系统的功能属性,即系统能够做什么,同时还应包含系统的非功能属性,即系统的质量如何.目前,通用的建模方法和工具对功能属性建模支持良好,而对如何为非功能属性建模关注得不多,特别是如何将二者统一起来并对描述的非功能属性的有关性质进行检验.通过在UML类图中增加非功能属性标注和约束关系表等建模元素来扩展UML类图,使其能够描述非功能属性.在此基础上,又提供了对扩展UML类图中非功能属性的一致性和可满足性进行检验的方法.通过实例对上述的面向非功能属     

并行设计的对象建模方法研究

基于对象的思想,以事件为核心分析了系统功能行为,提出了对象作业图与对象功能矩阵;论述了其作用与特性,阐述了利用这两个工具建立并行设计对象模型的方法与过程,使分析设计得到的类与对象具有完整性、一致性和客观性,提高了建立并行设计对象模型的有效性。     

基于UML的软件Markov链使用模型构造研究

软件统计测试要求基于软件使用模型产生测试例对软件系统进行测试,并根据测试结果评价软件可靠性,是高可靠软件测试的重要组成部分.由于统一建模语言(unified modeling language,简称UML)已经成为事实上的面向对象标准建模语言,因此,从软件UML模型构造软件使用模型就成为面向对象软件统计测试的关键.为此,定义了加入统计测试约束的UML用例图、序列图以及用例执行顺序关系,为基于UML的软件统计测试提供了一个形式化描述基础.在此基础上,给出一个从软件UML模型构造软件Markov链使用模型的算法,并给出了自动化支持工具UMGen的类图结构,基于一个卫星控制系统,说明了所提出方法的有效性.     

基于UML模型的全功能点自动化度量

软件规模在项目估算和决策中起着举足轻重的作用。基于软件需求从用户角度和功能角度度量规模的全功能点(FFP)广受欢迎，但为手工操作，弊端显而易见，所以亟需自动化度量。本文提出并实现了基于UML模型全功能点自动化度量系统，不但能得到精确的量化结果，而且能减轻工作量、降低花费，以及很大程度上避免抽取数据及度量过程中差错所造成的风险，更重要的是具有可重复性，从而易于功能规模度量方法的推广。