软件测试期末复习要点 第2章 软件开发过程与软件测试

本文介绍了软件工程的三个阶段及多种开发模型,阐述了软件测试的基本原则,如测试是为发现缺陷等。还对软件测试进行分类,包括静态、动态、黑盒、白盒、灰盒等测试,介绍了常用方法及优缺点,最后列举了五种测试过程模型。

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第2章 软件开发过程与软件测试

  1. 软件工程的三个阶段
    • 定义
    • 开发
    • 检验交付与维护
  2. 开发模型
    • 线性模型
    • 原型模型
    • 快速开发模型
    • 演化软件过程模型
      • 增量模型
      • 螺旋模型
  3. 软件测试基本原则
    1. 测试不是为了证明系统的正确性,而是为了证明系统存在缺陷
    2. 所有的测试都应该追溯到用户的需求
    3. 测试应当尽早开始和不断进行
    4. 穷举测试是不可能的
    5. 第三方测试会更客观、更有效
    6. Pareto原则应用于软件测试
    7. 软件测试是有风险的行为,但并非所有的测试都要修复
    8. 测试应从小规模开始,逐步转向大规模
    9. 软件测试是一项讲究条理的技术专业
  4. 软件测试分类
    • 静态测试(不运行软件)
    • 动态测试(运行被测试软件)
  5. 静态测试常用的方法有哪几种?
    1. 走查:是个非正式的过程,检查所有与源程序代码相关的文档。
    2. 审查:比走查要求更加正规。
    3. 静态代码分析工具:静态结构分析主要是以图形的方式表现程序的内部结构。
  6. 黑盒测试(功能测试、数据驱动测试)
    1. 特点:不考虑程序内部结构和处理过程
    2. 测试方法:
      1. 等价类划分
      2. 边界值法
      3. 决策表法
      4. 因果图法
    3. 优点
      • 测试用例与程序实现无关
    4. 缺点
      • 不能做穷举测试,可能存在漏洞
  7. 白盒测试(结构测试、逻辑驱动测试)
    1. 测试方法
      1. 逻辑覆盖
      2. 基本路径
      3. 数据流测试
    2. 优点
      1. 可以利用不同的覆盖准则测试程序代码的各个分支发现程序内部的编码错误
      2. 可以直接发现内存泄露问题
      3. 可以充当黑盒测试的检查手段等
    3. 局限性
      1. 程序路径组合太多,同样不能做到穷举测试
  8. 灰盒测试(白盒测试+黑盒测试)
  9. 人工测试与自动化测试(是否需要人工干预进行分类)
  10. 冒烟测试
  • 发现问题解决后,是否真的解决?对其他模块是否产生影响?
  1. 软件测试五种过程模型
    1. V-model
      • V-model模型软件测试的策略既包括低层测试又包括高层测试,底层测试是为了验证系统源代码的正确性,高层是为了测试整个系统是否满足用户的需求。
    2. W-model
      • 在V-model中增加软件各开发阶段应同步进行的测试,演化为W-model。
      • W-model的是测试伴随着整个软件开发周期,而且测试的对象不仅仅是程序,需求、功能和设计同样要测试。
    3. H-model
    4. X-model
    5. pretest-model
  2. 练习
    1. 软件测试的基本原则是什么?
    2. 软件测试方法怎样分类?
    3. 常见的软件测试过程模型有哪些?在实际测试工作中,怎样选择和使用相关模型?

2020年12月20日更

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Python Testing Cookbook Paperback: 364 pages Publisher: Packt Publishing (May 17, 2011) Language: English ISBN-10: 1849514666 ISBN-13: 978-1849514668 Over 70 simple but incredibly effective recipes for taking control of automated testing using powerful Python testing tools Learn to write tests at every level using a variety of Python testing tools The first book to include detailed screenshots and recipes for using Jenkins continuous integration server (formerly known as Hudson) Explore innovative ways to introduce automated testing to legacy systems Written by Greg L. Turnquist – senior software engineer and author of Spring Python 1.1 Part of Packt’s Cookbook series: Each recipe is a carefully organized sequence of instructions to complete the task as efficiently as possible In Detail Are you looking at new ways to write better, more efficient tests? Are you struggling to add automated testing to your existing system? The Python unit testing framework, originally referred to as “PyUnit” and now known as unittest, is a framework that makes it easier for you to write automated test suites efficiently in Python. This book will show you exactly how to squeeze every ounce of value out of automated testing. The Python Testing Cookbook will empower you to write tests using lots of Python test tools, code samples, screenshots, and detailed explanations. By learning how and when to write tests at every level, you can vastly improve the quality of your code and your personal skill set. Packed with lots of test examples, this will become your go-to book for writing good tests. This practical cookbook covers lots of test styles including unit-level, test discovery, doctest, BDD, acceptance, smoke, and load testing. It will guide you to use popular Python tools effectively and discover how to write custom extensions. You will learn how to use popular continuous integration systems like Jenkins (formerly known as Hudson) and TeamCity to automatically test your code upon check in. This book explores Python’s built-in ability to run code found embedded in doc strings and also plugging in to popular web testing tools like Selenium. By the end of this book, you will be proficient in many test tactics and be ready to apply them to new applications as well as legacy ones. A practical guide, this cookbook will ensure you fully utilize Python testing tools to write tests efficiently. What you will learn from this book : Get started with the basics of writing automated unit tests and asserting results Use Nose to discover tests and build suites automatically Write Nose plugins that control what tests are discovered and how to produce test reports Add testable documentation to your code Filter out test noise, customize test reports, and tweak doctest’s to meet your needs Write testable stories using lots of tools including doctest, mocks, Lettuce, and Should DSL Get started with the basics of customer-oriented acceptance testing Test the web security of your application Configure Jenkins and TeamCity to run your test suite upon check-in Capture test coverage reports in lots of formats, and integrate with Jenkins and Nose Take the pulse of your system with a quick smoke test and overload your system to find its breaking points Add automated testing to an existing legacy system that isn’t test oriented Approach This cookbook is written as a collection of code recipes containing step-by-step directions on how to install or build different types of Python test tools to solve different problems. Each recipe contains explanations of how it works along with answers to common questions and cross references to other relevant recipes. The easy-to-understand recipe names make this a handy test reference book. Who this book is written for Python developers and programmers with a basic understanding of Python and Python testing will find this cookbook beneficial. It will build on that basic knowledge equipping you with the intermediate and advanced skills required to fully utilize the Python testing tools. Broken up into lots of small code recipes, you can read this book at your own pace, whatever your experience. No prior experience of automated testing is required.
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