ucomxu 发表于 2021-11-14 16:02:27

软件项目的快速开发

编者按:越来越多的压力使得一个软件项目无论是最终用户、企业、开发团队都希望在最短的时间完成,可事与愿违的是软件项目的时间延期问题普遍存在,一些调查表明,70%的项目超出了估算的时间。大型项目平均超出计划交付时间的20%到50%,项目越大,超出计划的时间越长。一直以来开发速度的问题都是软件开发业的头等问题。那怎样才能在保证软件质量的同时又缩短开发速度呢?本期的《领航人》月刊中我们就将围绕着有关软件的“快速开发”主题来进行探讨。开发软件所需要经历的阶段  要谈“快速开发”我们就需要先来了解一下软件项目所需要经历的过程:  data:image/png;base64,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  软件的开发过程并不仅是一个编写、实现代码的简单过程,软件的开发需要经历许多的步骤。因此在开始时我们先用一个相对简单的方式了解一下软件开发的常见过程:data:image/png;base64,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   从上图可以直观的看出,一个软件的开发至少是包含了上图的三个阶段、七个步骤。  而这个过程中又可能涉及到下列各种参与软件开发的角色:data:image/png;base64,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[并不是任何项目中都会出现所有角色,角色同实际的参与人员也并不一定一一对应]  我们在此所探讨的软件“快速开发”为的是在软件目标、外部资源相同的情况下(如:同一团队,同一项目)可以缩减整个开发周期的各种方式,使软件项目最终能在一个更短时间内完成。data:image/png;base64,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能缩短软件开发周期的三种方式  缩短软件开发周期其实一直是全世界软件开发团队所长期关注的话题,把现在已被广泛认可的有效缩短周期的方式归类一下可划分为三大类:1. 工具快速 2. 模式快速 3. 经验快速   其分别代表着实现软件项目“快速开发”的“天时、地利、人和”,同时也蕴藏着“天时不如地利,地利不如人和”的真谛。天时——工具快速  在一个软件项目所经历的各阶段中(如:⑴需求分析、⑵原型开发、⑶实现、⑷测试、⑸完成、⑹需求变更、⑺后期维护),不同阶段选用适当的工具能非常直接的相应参与人员的工作效率、沟通效率,缩短单个步骤所需要的时间,从而在整体上缩短软件项目的开发周期。值得注意的一点是,工具并不仅限于软件形态的工具。  ⑴需求分析:是软件项目开发第一个也是很重要的一个阶段, 需求分析的基本任务是要准确地定义新系统的目标,为了满足用户需要,回答系统必须“做什么”的问题。 在这个阶段中包含需要获取需求、分析需求、编写规格说明和需求验证。从获取需求到需求验证的这个过程需要编写文档、绘制图形、创建需求模型等,像文档之类的工具可以使用word、绘制图形可以使用visio、建模可以使用rational rose等工具软件,有了这些工具的辅助,可提高编写文档的速度,缩短分析阶段的周期。除了以上这些软件形态的工具外还可为更快的项目参与人员之间的想法沟通,借助一些实体类工具,如纸制卡片,黑板或一些已经成型的系统。  ⑵原型开发:在软件需求分析阶段,需要搞清楚的是软件要“做什么”的问题,并把这些需求通过文档的形式描述出来,这也是目标系统的逻辑模型。进入设计阶段,则要把软件“做什么”的逻辑模型变换为“怎么做”的物理模型,即着手实现软件的需求,并将设计的结果反映在“设计规格说明”文档中,接下来开始设计。设计的基本任务包括:软件结构、数据结构及数据库设计、概要设计文档。开发一个大而复杂的软件系统,我们可以将它进行适当的分解来降低其复杂性,还可减少开发工作量,你也可以使用一些能够提高设计速的软件来帮助你进行设计,从而提高软件生产率,降低开发成本。所用的工具比如使用UML绘制类图的工具。  ⑶实现:设计完成之后进入编码实现阶段,为了提高整个项目的开发速度,编写代码我们可以借助一些有力的开发工具来加快速度,例如,如果是用JAVA语言开做开发的话,可以使用eclipse、JCreater,如果是用C#、VB你可以用Visual Studio.net;如果是开发网站之类的可以用Dreamweaver。美工可以使用photoshop或是FireWork之类的工具。节省项目的开发时间。另外一方面由于软件技术的快速发展带来了各种平台和引擎,选用适当的平台技术与引擎能更大程度的缩短周期。  ⑷测试:软件的测试也是一个非常重要的阶段,大量的测试,甚至重复的测试引出了一个新的问题:全凭手工进行测试会浪费大量的时间。因此,易变的需求对测试提出了一个新的要求:自动化测试。此类型的工具例如Xunit系列。只有自动化的进行测试,才可以完成大量的测试工作,节省时间和人力方面的投入,加快项目的整体开发速度。关于自动化测试这方面的问题,大家可以参考相关的资料,这里我们不作深入的讨论。  工匠用钉枪、成型砖块、涂料喷雾器来建造一个小屋的话要比他单纯用一把榔头、沙砖、涂料刷来得快。拥有快速交通工具的人可以比拥有普通交通工具的人提前到达目的地。但不论什么情况下,如果质量是非常重要的话,那么即使是强有力的工具也将会被手工工具所替代或辅助。软件开发中使用工具的情况与上述情况也是非常相近的。地利——模式快速  如前所说软件开发的过程并不是一个简单的过程,一个软件的开发会被分成很多步骤来实现,每一个步骤都有自己的起点和终点。也正如此使得开发过程中的每个步骤起点和终点在不同的软件项目中出现不同难度的“坎”,使其难于达到该步骤开始或是终结的条件,开发过程也就不会一帆风顺。  不同的开发模式其实就是将步骤的起点和终点重新定义,甚至重新组合排列,虽然任何一个开发模式最终目的都是完成软件项目的开发,但期间所经历的过程不一样,过程步骤之间的起点和终点的的定义不同所带来的“坎”也就不一样,项目周期自然各不相同,因此,根据软件项目的实际情况选择一个适合的开发模式能减少开发周期中“坎”的出现次数与难度,非常大程度的缩短开发周期。瀑布模型在本专题开始时我们所示范的开发流程,实际就是一种典型的瀑布模型(又称线形模型):data:image/png;base64,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瀑布模型是由W.W.Royce在1970年最初提出的软件开发模型,在瀑布模型中,开发被认为是按照需求分析,设计,实现,测试 (确认), 集成,和维护坚定地顺畅地进行。   在最初的文章中,Royce提倡重复地使用瀑布模型,以一种迭代的方式。但是,大多数人并不知道这一点,一些人也不相信它能够作为一种真实世界的过程使用。在实践中,过程很少能够以纯线性的方式进行。 通过回到前面的阶段或改便前一阶段的结果的迭代是非常普遍的。  线性模型太理想化,太单纯,以至很多人认为瀑布模型已不再适合现代的软件开发模式,几乎被业界抛弃。偶而被人提起,都属于被贬对象,未被留一丝惋惜。但我们应该认识到,“线性”是人们最容易掌握并能熟练应用的思想方法。当人们碰到一个复杂的“非线性”问题时,总是千方百计地将其分解或转化为一系列简单的线性问题,然后逐个解决。一个软件系统的整体可能是复杂的,而单个子程序总是简单的,可以用线性的方式来实现,否则干活就太累了。线性是一种简洁,简洁就是美。当我们领会了线性的精神,就不要再呆板地套用线性模型的外表,而应该用活它。   瀑布模型解决了软件工程上面的基本管理需求,但是对于我们所提的软件项目的“快速开发”瀑布模型并没有什么优势。 2.RUP(Rational Unified Process 瑞理统一过程)  RUP是建立在非常优秀的软件工程原则基础上的,例如迭代,需求驱动,基于结构化的过程开发。它提供了几个方法,例如每一次迭代产生一个工作原型,在每一个阶段的结束决定项目是否继续,这些方法提供了对开发过程的非常直观的管理。RUP采用了万维网技术,可以增强团队的开发效率,并为所有成员提供了最佳的软件实现方案。data:image/png;base64,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RUP处理过程为软件开发提供了规定性的指南、模板和范例。它可以通过提供一个应用于整个软件开发周期的、可定制的最佳开发方案架构,RUP可以对整个开发小组的工作进行指导和安排。RUP将项目管理、商业建模、需求管理、分析和设计、测试以及变更控制等,统一到了一个一致的、贯穿整个开发周期的处理过程。  RUP正如其名,它使团队中每个开发人员的见解和思想得到统一,使开发小组成员的沟通更为容易,而这正是任何项目要取得成功的关键因素;它增强了开发人员对软件的预见性,最终的好处就是提高了软件质量,并有效缩短了软件从开发到投放市场的时间,全面提高了开发速度。  RUP是严格按照行业标准UML开发的,它的特点主要表现为如下六个方面:· 开发复用。减少开发人员的工作量,并保证软件质量,在项目初期可降低风险。 · 对需求进行有效管理。 · 可视化建模。 · 使用组件体系结构,使软件体系架构更具弹性。 · 贯穿整个开发周期的质量核查。 · 对软件开发的变更控制。   RUP可以缩短软件项目的开发周期,实现大型项目的快速开发,对于中小型项目RUP就显的过于庞大,其需要投入的成本也很非常观。3.敏捷开发,极限编程  2001年,为了解决许多公司的软件团队陷入不断增长的过程泥潭,一批业界专家一起概括出了一些可以让软件开发团队具有快速工作、响应变化能力的价值观和原则,他们称自己为敏捷联盟。敏捷开发过程的方法很多,主要有:SCRUM,Crystal,特征驱动软件开发(Feature Driven Development,简称FDD),自适应软件开发(Adaptive Software Development,简称ASD),以及最重要的极限编程(eXtreme Programming,简称XP)。  极限编程是一套能快速开发高质量软件所需的价值观、原则和活动的集合,使软件能以尽可能快的速度开发出来并向客户提供最高的效益。XP在很多方面都和传统意义上得软件工程不同,同时,它也和传统得管理和项目计划得方法不同。这些方法在软件工程和其他管理活动中都有借鉴意义。XP具有12个过程,只有完全使用12个过程才是真正使用了XP,只是简单使用了其中一个方法并不代表使用了XP。· 现场客户(On-site Customer) · 计划博弈(Planning Game) · 系统隐喻(System Design) · 简化设计(Simple Design) · 集体拥有代码(Collective Code Ownership) · 结对编程(Pair Programming) · 测试驱动(Test-driver) · 小型发布(Small Release) · 重构(Refactoring) · 持续集成(Continous integration) · 每周40小时工作制(40-hour Weeks) · 代码规范(Coding Standards)   下面是极限编程的有效实践:1. 完整团队 XP项目的所有参与者(开发人员、客户、测试人员等)一起工作在一个开放的场所中,他们是同一个团队的成员。这个场所的墙壁上随意悬挂着大幅的、显著的图表以及其他一些显示他们进度的东西。 2. 计划游戏计划是持续的、循序渐进的。每2周,开发人员就为下2周估算候选特性的成本,而客户则根据成本和商务价值来选择要实现的特性。1. 客户测试作为选择每个所期望的特性的一部分,客户可以根据脚本语言来定义出自动验收测试来表明该特性可以工作。 2. 简单设计团队保持设计恰好和当前的系统功能相匹配。它通过了所有的测试,不包含任何重复,表达出了编写者想表达的所有东西,并且包含尽可能少的代码。 3. 结对编程所有的产品软件都是由两个程序员、并排坐在一起在同一台机器上构建的。 4. 测试驱动开发编写单元测试是一个验证行为,更是一个设计行为。同样,它更是一种编写文档的行为。编写单元测试避免了相当数量的反馈循环,尤其是功功能能验证方面的反馈循环。程序员以非常短的循环周期工作,他们先增加一个失败的测试,然后使之通过。 5. 改进设计随时利用重构方法改进已经腐化的代码,保持代码尽可能的干净、具有表达力。 6. 持续集成团队总是使系统完整地被集成。一个人拆入(Check in)后,其它所有人责任代码集成。 7. 集体代码所有权任何结对的程序员都可以在任何时候改进任何代码。没有程序员对任何一个特定的模块或技术单独负责,每个人都可以参与任何其它方面的开发。 8. 编码标准 系统中所有的代码看起来就好像是被单独一人编写的。 9. 隐喻 将整个系统联系在一起的全局视图;它是系统的未来影像,是它使得所有单独模块的位置和外观变得明显直观。如果模块的外观与整个隐喻不符,那么你就知道该模块是错误的。 10. 可持续的速度 团队只有持久才有获胜的希望。他们以能够长期维持的速度努力工作,他们保存精力,他们把项目看作是马拉松长跑,而不是全速短跑。 极限编程是一组简单、具体的实践,这些实践结合在形成了一个敏捷开发过程。极限编程是一种优良的、通用的软件开发方法,项目团队可以拿来直接采用,也可以增加一些实践,或者对其中的一些实践进行修改后再采用。 4.NoahWeb"增量迭代"模式  以RUP和极限编程中的增量所不同的的是NoahWeb“增量迭代”模式仅适用于B/S软件项目。考虑B/S项目中的人员配置、工作重心与C/S项目截然不同的特殊性,因此该模式专门针对B/S项目而提出。  从以往的很多B/S应用开发案例来看,用户的需求并不会在需求分析阶段和原型开发阶段就可以准确获得,往往在应用系统接近发布时,用户才会提出各种各样具体的需求。data:image/png;base64,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
  导致这样的原因很简单:在需求分析阶段,最终用户不可能通过开发文档就能想象出应用系统运行时的实际情况,而系统接近成型时,用户通过真实使用会感觉到系统存在的问题和设计缺陷。由于用户需求在发布前频繁变更这一特性,使用传统B/S解决方案的设计人员和开发人员将会此阶段面临需求变更的各种考验,项目周期和开发成本也会在发布阶段由于需求变更急剧扩大,有时甚至可能之前工作推倒从来。· 考虑B/S项目的特殊性   B/S项目以往一直采用同C/S软件项目一样的开发模式和流程管理。但由于B/S项目同C/S项目太多的不同之处,使得B/S项目开发 周期很难控制。B/S一方面要面临着需要短时间获取需求,需求不明确。另一方面B/S开发中美工和界面设计美化的重要性也不同于C/S项目,B/S项目往往由美术和程序两方面的人员来决定需求并且相互制约,这些巨大区别似的不能将B/S项目等同与C/S项目来进行管理。  NoahWeb“增量迭代”开发模式的各步骤特点如下:· 用“迭代”探索需求 o 需求分析阶段:   设计人员关注的不是程序结构设计,而是用户流程,在需求分析阶段就可以邀请用户一起参与“动作分解图”的设计,让用户从一开始就可以感受到软件使用的流程,让所开发的软件从一开始就贴近用户需求;· 原型阶段:   原型阶段将整个软件项目的数据输入界面和输出按照动作流程呈现给用户,让用户可以直观的从输入输出的具体细节体验软件,反馈修改意见,让开发的软件再次贴近需求。· 实现阶段   在此阶段,还可以让用户通过至少两个阶段性的演示让用户体会软件的流程和真实的数据输入输出,体验真实的软件使用感觉,为项目开发团队反馈出更准确的需求。· 发布阶段 在发布阶段软件已经能非常贴近最终用户需求,即使发布后更意外的需求变更,也能轻松应变。  使用该模式项目实施B/S项目的效果将很大程度上区别于其他模式效果。软件项目的开发中需求分析与编码实现已经被融为一体,而且在开发的任意阶段,开发人员都已经准备好应付后续阶段可能出现的任何变化。变化成为计划一部分。
页: [1]
查看完整版本: 软件项目的快速开发