2018测试趋势

原文链接

Recent years have brought many changes to software testing practices that will define 2018, such as DevOps adoption, combined automated and manual testing, and more.

近年的软件测试实践上发生的很多变化会决定2018年的趋势，比如DevOps的使用，自动化和手工测试的融合等。

The software testing community has experienced the exciting year of 2017 with many trends taking shape. Amid both hypes and actual applications of artificial intelligence (AI) and automation, many developments and challenges in software testing through the year deserve our attention. They include a continuing trend in adoption of DevOps and test automation practices and tools, increasing test automation for web applications along with new and more powerful test automation tools introduced to the market, remaining difficulties in managing test data and environments, shortening release schedules, and the lack of time for testing.

软件测试社区经历了2017年激动人心的一年, 许多趋势正在形成。在人工智能 (AI) 、自动化的炒作及应用中, 也有许多软件测试中的发展和挑战值得我们关注。它们包括以下持续上升的趋势：DevOps的应用、测试自动化实践和工具, 更多新的、更强大的测试自动化工具在web自动化测试的使用。同时我们在测试数据和环境管理, 缩短发布时间表, 以及缺少测试时间等方面还存在很多困难。

In reference to the state of software testing in 2017, we here make bold predictions of trends of software testing for 2018 and beyond.

参考2017年的软件测试业现状, 这里对2018和以后的软件测试趋势进行以下大胆的预测。

1. Increasing Adoption of DevOps
   DevOps is a set of practices that aim to reduce the time from development (Dev) to operation (Ops) while ensuring the quality of software. According to Google Trends, as shown in the figure below, DevOps has gained an overwhelming interest over the past five years. This trend likely continues in the next few years. We will see more organizations employing DevOps practices more fully. As DevOps practices emphasize on automation and integration, more practices and tools are introduced to support automated testing and continuous integrations.

1. 越来越多地采用 DevOps

DevOps是一组旨在在确保软件质量的同时缩短开发 (dev) 到操作 (Ops) 的时间的实践。根据Google trend, 如下图所示, DevOps 在过去五年中获得了显著的关注，这一趋势可能在未来几年还将继续。我们将看到更多的组织更充分地使用 DevOps 实践。随着 DevOps 实践强调自动化和集成, 将引入更多的实践和工具来支持自动化测试和持续集成。

2. More Utilization of Test Automation
   Although test automation is an essential part of DevOps, it currently only accounts for less than 20% of software testing activities according to World Quality Report 2017 - 2018. Organizations mainly focus on functional UI and regression testing.
   Test automation is seen as the main approach to shortening the testing and delivery time. The capability to integrate with DevOps toolchains becomes a must-have feature of test automation tools. Most major open-source and free tools such as Selenium and Katalon and commercial tools as Ranorex and TestComplete now support integration with many DevOps toolchains like Jenkins, GIT, and JIRA.

2. 自动化测试的更多应用

尽管测试自动化是 DevOps 的一个重要部分, 但根据 2017-2018 的《世界质量报告》, 它只在软件测试活动占比不到20% 。组织更多关注在功能性 UI 和回归测试上。 一般认为自动化测试是缩短测试和交付时间的主要方法。与 DevOps 工具链集成的能力成为测试自动化工具的一个必须具备的功能。大多数主流开源和免费工具如selenium和 Katalon, 以及商业工具, 如 Ranorex 和 TestComplete 现在支持集成与许多 DevOps 工具链如Jenkins, GIT 和 JIRA。

3. Combining Manual and Automated Testing
   Although test automation is a hot keyword today, manual testing is still dominating in the QA and testing industry. This state of software testing makes it hard to address challenges in ever shortening delivery cycles and complex test environments and data. Combining manual and automated testing practices and tools is likely a continuing trend in the next few years. Right testing strategies are those that take advantages of both manual and automated approaches.

3. 手工测试和自动化测试的融合

尽管测试自动化是当今的热门, 但在 QA 和测试行业, 手动测试仍处于主导地位。这种软件测试的状态使得应对缩短交付周期、复杂的测试环境和数据方面的挑战很困难。融合手动和自动化测试实践和工具可能是未来几年的持续趋势。正确的测试策略是同时利用手工和自动化方法的优点。

4. Intelligent Test Automation and Analytics
   AI and machine learning techniques have been applied to software development to improve the productivity of project teams and quality of software. Given recent advancements and growing applications of AI and ML in practice, there will be more intelligent test automation technologies and tools that are smarter in generating test cases, test scripts, test data, and in maintaining and reusing test scripts. They would also bring advancements to formulating test scenarios, predicting application behaviors, and predicting areas and levels of test. Intelligent testing tools will need to offer smart analytics to help better diagnose faults and visualize test results and overall product quality using multi-source data.
   Refer to the Dzone report for the Best 10 automation testing tools that cannot be missed in 2018.

4. 智能自动化测试及分析

AI和机器学习技术已应用到软件开发中来提高项目团队的生产率和软件质量。鉴于人工智能和 机器学习 在实践中的最新进展和越来越多的应用, 将会有更多的智能测试自动化技术和工具, 它们在生成测试用例、测试脚本、测试数据以及维护和重用测试脚本方面更聪明。它们还将为制定测试方案、预测应用程序行为和预测测试领域和水平带来进步。智能测试工具需要提供智能分析, 以帮助更好地诊断故障, 并使用多源数据来使测试结果和整体产品质量可视化。 请参阅 Dzone 报告:2018不能错过的十大自动化测试工具

5. Increasing Mobile Test Automation
   The utilization of test automation in software projects is now at a low level. For mobile test automation, it is even lower. There is a current lack of right methods, tools, and devices to perform automated testing of mobile applications. The increasing shift away from desktop and web towards mobile applications along with ever shortening time-to-market requires software organizations to increase the application of test automation for mobile applications. Emerging mobile test platforms and tools such as Kobiton and Sauce Labs may offer advanced and right capabilities to make mobile test automation more executable and affordable.

5. 移动端自动化测试的增长

软件项目中测试自动化的使用现在处于低水平。对于移动测试自动化来说甚至更低。当前缺少对移动应用程序进行自动测试的正确方法、工具和设备。随着越来越多的桌面和网络应用转向移动应用且要求更短的上市时间, 软件组织需要增加对移动应用程序的测试自动化的应用。新兴的移动测试平台和工具, 如 Kobiton 和Sauce Labs, 可能提供先进和正确的能力, 使移动测试自动化更可执行和负担得起。

6. Shortening Delivery Cycles
   Rapid changes in technologies, platforms, and devices pressure software development teams to develop, test, integrate, and deliver faster and more frequently. Software needs to be delivered and deployed daily instead of monthly or weekly. Software organizations will invest more in improving their development and delivery processes and methods as well as employing a right set of DevOps tools. This demand will derive the growth of DevOps practices and tools which leads to further utilization of test automation in QA and testing.

6. 更短的交付周期

技术、平台和设备的快速变化迫使软件开发团队开发、测试、集成和交付速度要更快、更频繁。软件需要每天交付和部署, 而不是每月或每周。软件组织将更多地投资于改进其开发和交付过程和方法以及使用一套正确的 DevOps 工具。这种需求将产生 DevOps 实践和工具的增长, 从而进一步利用测试自动化进行 QA 和测试。

7. API and Services Test Automation
   The main utilization of test automation now focuses on UI testing. A majority of API and services testing is currently performed by developers manually. The trend will be an increasing application of automating API and services testing processes, at a greater pace than automating the UI testing process. Independent testers who are equipped with intelligent and easy-to-use tools will be responsible for API and services testing, helping to reduce time-to-market while improving software quality.

7.API 和服务测试自动化

测试自动化的主要用途现在侧重于 UI 测试。大多数 API 和服务测试当前由开发人员手动执行。一个大趋势是自动化 API 和服务测试会更多地应用, 它比自动化 UI 测试过程的速度更快。拥有智能、易用工具的独立测试人员将会负责 API 和服务测试, 帮助减少市场时间, 同时提高软件质量。

8. Integration
   To support smart testing and analytics, data has to be gathered from different sources and phases in software development, such as requirements management systems, change control systems, task management systems, and test environments. We will see test automation and management tools offering features to integrate with various ALM toolsets and test environments. This integration allows smarter decision-making concerning software testing and quality.

8.集成

为了支持智能测试和分析, 必须从软件开发的不同来源和阶段收集数据, 例如需求管理系统、变更控制系统、任务管理系统和测试环境。我们将看到测试自动化和管理工具提供的功能, 以集成各种 ALM 工具集和测试环境。这种集成允许在软件测试和质量方面进行更明智的决策。

This article offers the bold predictions of trends in the next few years. As any prediction can be wrong, the trends here may suggest opportunities and challenges for us in the software industry.

这篇文章提供了对未来几年趋势的大胆预测。由于任何预测都可能是错误的, 这里的趋势可能给我们在软件行业带来机遇和挑战。