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原文作者信息: Mathias Lother, Reiner R. Dumke University of Magdeburg, Dept. of Computer Science, Postfach 4120, 39016 Magdeburg, Germany, Tel.: +49-391-67-18664, Fax: +49-391-67-12810, Email: {lother,dumke}@ivs.cs.uni-magdeburg.de, http://ivs.cs.uni-magdeburg.de/sw-eng/us/ 5. 可供选择的功能规模度量方法 相对于传统的规模度量方法,出现了一些新的方法。本章将简单介绍三种最近提出的新提法: 预言性的对象点( Predictive Object Points), 组件重用制(Component Reuse Metrics ), 构件点(Construction Points) 5.1预言性的对象点(Predictive Object Points) 在意识到传统的软件度量方法不足以适用于面向对象软件的生产力跟踪和工作量预测后,预言性的对象点方法被开发了[38][39]。 预言性的对象点方法是特别为面向对象软件设计的度量方法并且它是通过度量系统的面向对象属性得到结果。预言性对象点方法满足第4.5节所提到的重用包含问题,因为它度量软件传递的原始功能数,包括对象间的交流信息和通过继承的重用。预言性对象点方法的核心是Chidember和Kemerer提出的每类权重度量方法(the Weighted Methods per Class metric),但也受到面向对象度量方法继承树深度方法(Depth of Inheritance Tree DIT)和子类数方法(Number of Children NOC)的影响。实际情况是提供一个面向对象和工作量之间对数据研究的联系,这是通过度量和计算过程研究结果。但仍有障碍需要克服。需要收集额外的数据和修正原始结果。 另外一点是填补在早期分析过程中可能的工作产品和预言性对象度量计算需要的缺口。更进一步是考虑用例作品和预言性对象点之间的直接关系和自动度量过程。 推荐读物: [38],[39] 5.2 组件重用度量方法(Component Reuse Metric) Virtanen提出了一种估计软件开发工作量的新方法[40][41]。组件重用方法综合了面向对象组件技术的最好方法和对人类行为(技能,动机,团队影响)的分析而形成简单计算规则。组件重用方法用不同种类的组件数来表示软件规模,并认为这些数字是不可加的。而且这种方法考虑的风险的影响,特别是风险未来蔓延的影响也考虑了。用组件自己代替一些规模度量单位来表示规模是组件重用方法一个不同的特点,另外一个特点是它对人的影响作用的重要估价。 任务的基本估计大多数用工作量估计方法,最重要是窗口数和数据表的个数的度量。组件重用方法可以看成这种方法的扩展。根据有关案例研究情况,在没有经验和历史数据,估计项目和人的影响作用是困难的。但依照Virtanen观点,很明显,如果这些估计是准确的,组件重用将是一个非常正确的方法。为了发布产品(译者注:这种方法的发布)必须进行进一步研究。 推荐读物: [40], [41] 5.3 构件点(Construction Points) Victor和Daily提出了一种所谓构件点的能估计作业叫SPECTRE的方法[42]。她的目的是预测开发任务时间和模块规模,这些都和项目因素如任务内容和复杂度以及开发人员的知识和经验等非常敏感。 这种方法在路线上和功能点分析方法有些相似,但目标实体上有区别,功能点分析是面向项目而构件点是面向任务的测量制度。构件点是基于许多年的经验积累观察,而且依照Victor 和Daily说法,她有众所周知的可检查的准确性。 SPECTRE 利用她的构件点能有效地应用于完善地任务说明,事实上,她也可以方便地应用于整个开发过程的任务规范。 推荐读物: [42] 6. 总结 本文选择介绍了几种重要的功能规模度量方法,并就适用性和成熟度方面对他们进行了评价。紧接着,本文提出并讨论了功能规模度量方法的共性问题,如自动计算、可兑换问题等。随后文章介绍了可供选择的最近发布的功能规模度量方法。可以得出这样的结论:功能规模度量对软件开发来说很重要,但是有几个问题必须的考虑,如方法在功能业务领域的适用性,新技术的影响等。另外一个结论是对功能规模度量方法的共性问题还需要大量的调查和研究,如: 不同功能规模度量方法之间的可兑换性, 功能点和UML之间的映射, 在规则系统/科学系统软件方面的度量 , 总之, 建立一种能作为度量独立领域并且利用所有软件生命周期阶段产物而得到度量输入的国际标准的规模度量方法是悦人心意的。 7. 参考文献 [01] Capers Jones, "Applied Software Measurement – Assuring Productivity and Quality", McGraw-Hill, New York, 1991. 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