[ZZ]From QA to Engineering Productivity
http://googletesting.blogspot.com/2016/03/from-qa-to-engineering-productivity.html
In Google’s early days, a small handful of software engineers built, tested, and released software. But as the user-base grew and products proliferated, engineers started specializing in roles, creating more scale in the development process:
- Test Engineers (TEs) -- tested new products and systems integration
- Release Engineers (REs) -- pushed bits into production
- Site Reliability Engineers (SREs) -- managed systems and data centers 24x7.
This story focuses on the evolution of quality assurance and the roles of the engineers behind it at Google. The REs and SREs also evolved, but we’ll leave that for another day.
Initially, teams relied heavily on manual operations. When we attempted to automate testing, we largely focused on the frontends, which worked, because Google was small and our products had fewer integrations. However, as Google grew, longer and longer manual test cycles bogged down iterations and delayed feature launches. Also, since we identified bugs later in the development cycle, it took us longer and longer to fix them. We determined that pushing testing upstream via automation would help address these issues and accelerate velocity.
As manual testing transitioned to automated processes, two separate testing roles began to emerge at Google:
- Test Engineers (TEs) -- With their deep product knowledge and test/quality domain expertise, TEs focused on what should be tested.
- Software Engineers in Test (SETs) -- Originally software engineers with deep infrastructure and tooling expertise, SETs built the frameworks and packages required to implement automation.
The impact was significant:
- Automated tests became more efficient and deterministic (e.g. by improving runtimes, eliminating sources of flakiness, etc.)
- Metrics driven engineering proliferated (e.g. improving code and feature coverage led to higher quality products).
Manual operations were reduced to manual verification on new features, and typically only in end-to-end, cross product integration boundaries. TEs developed extreme depth of knowledge for the products they supported. They became go-to engineers for product teams that needed expertise in test automation and integration. Their role evolved into a broad spectrum of responsibilities: writing scripts to automate testing, creating tools so developers could test their own code, and constantly designing better and more creative ways to identify weak spots and break software.
SETs (in collaboration with TEs and other engineers) built a wide array of test automation tools and developed best practices that were applicable across many products. Release velocity accelerated for products. All was good, and there was much rejoicing!
SETs initially focused on building tools for reducing the testing cycle time, since that was the most manually intensive and time consuming phase of getting product code into production. We made some of these tools available to the software development community: webdriver improvements, protractor, espresso, EarlGrey, martian proxy,karma, and GoogleTest. SETs were interested in sharing and collaborating with others in the industry and established conferences. The industry has also embraced the Test Engineering discipline, as other companies hired software engineers into similar roles,published articles, and drove Test-Driven Development into mainstream practices.
Through these efforts, the testing cycle time decreased dramatically, but interestingly the overall velocity did not increase proportionately, since other phases in the development cycle became the bottleneck. SETs started building tools to accelerate all other aspects of product development, including:
- Extending IDEs to make writing and reviewing code easier, shortening the “write code” cycle
- Automating release verification, shortening the “release code” cycle.
- Automating real time production system log verification and anomaly detection, helping automate production monitoring.
- Automating measurement of developer productivity, helping understand what’s working and what isn’t.
In summary, the work done by the SETs naturally progressed from supporting only product testing efforts to include supporting product development efforts as well. Their role now encompassed a much broader Engineering Productivity agenda.
Given the expanded SET charter, we wanted the title of the role to reflect the work. But what should the new title be? We empowered the SETs to choose a new title, and they overwhelmingly (91%) selected Software Engineer, Tools & Infrastructure (abbreviated to SETI).
Today, SETIs and TEs still collaborate very closely on optimizing the entire development life cycle with a goal of eliminating all friction from getting features into production. Interested in building next generation tools and infrastructure?
[ZZ]From QA to Engineering Productivity的更多相关文章
- (转)Engineering Productivity
(转)http://www.wandoujia.com/blog/from-qa-to-ep 这个文章之前读过,很不错.今天再读,有不一样的感受!推荐下. 下面是几段摘录: EP 是什么 说到这里,E ...
- 【转】从QA到EP
从QA到EP 两三年以前,和友人谈到 QA(软件质量保证) 这个行业,还有 QA 这个团队的未来,就有了一丝忧虑.而现在,终于有机会实践一下自己之前的想法,在这里分享给大家. 从我有限的从业经验到现在 ...
- 从QA到工程能效团队
Engineering Productivity Productivity is our job; testing and quality are the job of everyone involv ...
- 从 QA 到 EP
两三年以前,和友人谈到 QA(软件质量保证) 这个行业,还有 QA 这个团队的未来,就有了一丝忧虑.而现在,终于有机会实践一下自己之前的想法,在这里分享给大家. 从我有限的从业经验到现在,经历了很多次 ...
- <自动化测试方案_9>第九章、持续集成平台搭建
第九章.持续集成平台搭建 (一)什么是持续集成 参考文章地址:https://blog.csdn.net/qq_32261399/article/details/76651376 敏捷软件开发(英语: ...
- CI/CD持续集成/持续部署 敏捷开发
敏捷软件开发(英语:Agile software development),又称敏捷开发,是一种从1990年代开始逐渐引起广泛关注的一些新型软件开发方法,是一种应对快速变化的需求的一种软件开发能力.它 ...
- Docker与CI持续集成/CD
背景 Docker 是一个开源的应用容器引擎,让开发者可以打包他们的应用以及依赖包到一个可移植的容器中,然后发布到任何流行的 Linux 机器上,也可以实现虚拟化.容器是完全使用沙箱机制 ...
- 小课堂week14 Google软件测试之道
读<Google软件测试之道> 在IT领域,Google是一面旗帜,是一家非常善于思考善于尝试的公司.随着面临挑战的不断增大,传统的测试开展方式也越来越力不从心,这本书讲述的就是一次完整的 ...
- 前后端分离 接口管理神器——Rap本地搭建
我这里要用做mockserver的就是rap了,rap结合了团队管理,项目管理,文档编写.Mock.js.可视化.接口过渡.文档历史版本(赞).mock插件(线上线下切换就只需要注释一句代码就OK), ...
随机推荐
- 设计模式(四)抽象工厂模式(Abstract Factory Pattern)
一.引言 在上一专题中介绍了工厂方法模式,工厂方法模式是为了克服简单工厂模式的缺点而设计出来的,简单工厂模式的工厂类随着产品类的增加需要增加额外的代码,而工厂方法模式每个具体工厂类只完成单个实例的创建 ...
- 基础笔记(三):网络协议之Tcp、Http
目录 一.网络协议 二.TCP(Transmission Control Protocol,传输控制协议) TCP头格式 TCP协议中的三次握手和四次挥手 TCP报文抓取工具 三.HTTP(Hyper ...
- 零基础如何学习java更有效呢?
零基础学java,不知道该如何入手?也不知道学习的方向,很多人会问零基础怎么样学习,有没有什么入门的书籍推荐:只要方法正确,零基础学好java也是有机会的哦. 一.理解Java思想 Java是一门面向 ...
- Laravel安装方法 (windows)
Laravel安装方法(windows) 安装PHP 下载PHP7 http://windows.php.net/download#php-7.0 进入上述网站下载PHP7 选择zip包解压安装 配置 ...
- ABP之动态WebAPI(二)
HttpControllerDescriptor与HttpActionDescriptor HttpControllerDescriptor封装了某个HttpController类型的元数据,我们可以 ...
- 原型对象prototype和原型属性[[Prototype]]
构造器:可以被 new 运算符调用, Boolean,Number,String,Date,RegExp,Error,Function,Array,Object 都是构造器,他们有各自的实现方式. 比 ...
- 软件开发流程 Software development process
软件开发流程(Software development process)即软件设计思路和方法的一般过程,包括设计软件的功能和实现的算法和方法.软件的总体结构设计和模块设计.编程和调试.程序联调和测试以 ...
- js 数组去重(7种)
第一次写技术博客,之前总是认为写这些会很浪费时间,还不如多看几篇技术博文.但...但昨天不知道受了什么刺激,好像有什么在驱使着自己要写一样,所以才有了今天的第一篇博文.总觉得应该要坚持这样写下去.初次 ...
- jquery简介和实例
一.简介 定义 jQuery创始人是美国John Resig,是优秀的Javascript框架: jQuery是一个轻量级.快速简洁的javaScript库. 参考:http://www.php100 ...
- Oracle a Parameter with multi value
备注:此两种方案,都因为oracle内部字符函数的参数长度4000限制.另外,个人测试,性能不如”将数据插入物理表再JOIN查询“或”每1000次ID做一次IN查询“的总的运行速度. 即ID的个数越 ...