将自动化测试推向极限
目录
翻译内容
Pushing the limits 推动极限
The promise of artificial intelligence in automated testing 人工智能在自动化测试中的承诺
Manual practices remain 手动操作保留
Robotic process automation 机器人过程自动化
关于作者
About Christina Cardoza
原链接
翻译内容
The software industry keeps expressing it is under immense pressure to keep up with market demand and deliver software faster. Automated testing is an approach that came out to not only help speed up software delivery, but to ensure the software that did come out did what it was supposed to do. For some time automated testing has been great at removing repetitive manual tasks, but the industry is only moving faster and businesses are now looking for ways to do more.
软件行业一直表示，它正面临着跟上市场需求和更快地交付软件的巨大压力。 自动化测试是一种不仅有助于加速软件交付，而且确保已经完成的软件能够完成预期的软件的方法。 一段时间以来，自动化测试在删除重复的手动任务方面做得非常出色，但行业发展速度更快，企业现在正在寻找更多方法。
“Rapid change and accelerating application delivery is a topic that used to really be something only technology and Silicon Valley companies talked about. Over just the past few years, it has become something that almost every organization is experiencing,” said Lubos Parobek, vice president of product for the testing company Sauce Labs. “They all feel this need to deliver apps faster.”
“过去，快速变革和加速应用交付是一个真正只是技术和硅谷公司谈论的话题。 在过去的几年里，它已经成为几乎每个组织都在经历的事情，“测试公司Sauce Labs产品副总裁Lubos Parobek说。 “他们都觉得这需要更快地提供应用程序。”
This sense of urgency has businesses looking to leverage test automation even further and go beyond just automating repetitive tasks to automating in dynamic environments where everything is constantly changing. “As teams start releasing even weekly, let alone daily or multiple times a day, test automation needs to change. Today test automation means ‘automation of test execution,’ but the creation and maintenance of tests, impact analysis and the decision of which test to run, the setup of environments, the reviewing of results, and the go/no-go decision are all entirely manual and usually ad-hoc,” said Antony Edwards, CTO of the test automation company Eggplant. “The key is that test automation needs to expand beyond the ‘test execution’ boundary and cover all these activities.”
这种紧迫感使企业希望进一步利用测试自动化，不仅仅是将重复性任务自动化，而是在一切都在不断变化的动态环境中实现自动化。 “随着团队每周开始发布，更不用说每天或多次，测试自动化需要改变。 今天，测试自动化意味着“测试执行的自动化”，但是测试的创建和维护，影响分析以及决定运行哪个测试，环境设置，结果审查以及决定/不决定都是完全是手动的，通常是临时的，“测试自动化公司Eggplant的首席技术官Antony Edwards说。 “关键是测试自动化需要超越'测试执行'的范围，并涵盖所有这些活动。”
Pushing the limits 推动极限
Perhaps the biggest drivers for test automation right now are continuous integration, continuous delivery, continuous deployment and DevOps because they are what is pushing organizations to move faster and get software into the hands of their users more quickly, according Rex Black, president of the Rex Black Consulting Services, a hardware and software testing and quality assurance consultancy.
Rex Black Consulting Services，一家硬件和软件测试和质量保证咨询公司。其总裁Rex Black表示，目前测试自动化的最大推动因素可能是持续集成，持续交付，持续部署和DevOps，因为它们正在推动组织更快地前进，并更快地将软件交付给用户。
“But the only way for test automation to provide value and to not be seen as a bottleneck is for it to be ‘continuous,’” said Mark Lambert, vice president of products at the automated software testing company Parasoft.
“但测试自动化提供价值，并且不被视为瓶颈的唯一方法是让它变得'连续'，”自动化软件测试公司Parasoft产品副总裁Mark Lambert说。
According to Lambert, this happens in two ways. First, the environment has to be available at all times so tests can be executed at anytime and anywhere. Secondly, the tests need to take change into account. “Your testing strategy has to change resistance built into it. Handling change at the UI level is inherently difficult, which is why an effective testing strategy relies on a multi-layer approach. This starts with a solid foundation of fully automated unit tests, validating the granular functionality of the code, backed up with broad coverage of the business logic using API layer testing,” said Lambert. “By focusing on the code and API layers, tests can be automatically refactored leaving a smaller set of the brittle end-to-end UI level tests to manage.”
根据Lambert的说法，这有两种方式。 首先，环境必须始终可用，因此可以随时随地执行测试。 其次，测试需要考虑变化。 “你的测试策略必须改变内置的阻力。 在UI级别处理变更本身就很困难，这就是为什么有效的测试策略依赖于多层方法的原因。 这开始于全面自动单元测试的坚实基础，验证代码的细化功能，使用API层测试对业务逻辑的广泛覆盖进行备份，“Lambert说。 “通过专注于代码和API层，可以自动重构测试，留下一小部分脆弱的端到端UI级别测试需要管理。”
Part of that strategy also means having to look at testing from a different angle. According to Eggplant’s Edwards, testing has shifted from testing to see if something is right, to testing to see if something is good. “I am seeing more and more companies say, ‘I don’t really care if my product complies with a [specification] or not,’ ” he said. “No one wants to be the guy saying no one is buying our software anymore, and everyone hates it, but at least it complies with the spec.” Instead, testing is shifting from thinking about the requirements to thinking about the user. Does the software increase customer satisfaction, and is it increasing whatever the business metric is you care about?
该策略的一部分还意味着必须从不同角度看待测试。 根据Eggplant的Edwards的说法，测试已经从测试转移到看看是否正确，测试是否有好的东西。 “我看到越来越多的公司说，'我真的不在乎我的产品是否符合[规格]，'”他说。 “没有人愿意成为这样一个人，说不再有人在购买我们的软件，而且每个人都讨厌它，但至少它符合规范。”相反，测试正在从思考需求转向思考用户。 该软件是否提高了客户满意度，并且无论您关心的业务指标是什么，它是否会增加？
“If you care about your user experience, if you care about business outcome, you need to be testing the product form the outside in, the way a user does,” Edwards added.
“如果你关心你的用户体验，如果你关心业务成果，你需要从外面测试产品，就像用户一样，”Edwards补充说。
Looking at it from the user’s side involves monitoring performance and the status of a solution in production. While that may not seem like it has anything to do with testing or automation, it’s about creating automated feedback loops and understanding the technical behavior of a product and the business outcome, Edwards explained. For example, he said if you look at the page load speed of all your pages and feed that back into testing, instead of automating tests that say every page has to respond in 2 seconds, you can get more granular and say certain pages need to load faster while other pages can take up to 10 seconds and won’t have a big impact on experience.
从用户方面来看，涉及监控性能和生产中的方案的状态。 Edwards解释说，虽然这似乎与测试或自动化无关，但它是关于创建自动反馈循环，并理解产品的技术行为和业务成果。 例如，如果你查看所有页面的页面加载速度并将其反馈到测试中，而不是自动化测试，表明每个页面必须在2秒内响应，你可以更精细地说出某些页面需要更快加载，而其他页面最多可能需要10秒，并且不会对体验产生很大影响。
“Testing today is too tied to the underlying implementation of the app or website. This creates dependencies between the test and the code that have nothing to do with verification or validation, they are just there because of how we’ve chosen to implement test automation,” Edwards said.
“今天的测试，与应用程序或网站的底层实现关系紧密。 这会在测试和代码直接产生依赖，这些代码指与确认或验证无关的代码之，因为我们选择实施测试自动化，这些依赖就会存在，“Edwards说。
But just because you aren’t necessarily testing something against a specification anymore, doesn’t mean you shouldn’t be testing for quality, according to Thomas Murphy, senior director analyst at the research firm Gartner. Testing today has gone from a calendar event to more of a continuous quality process, he explained.
研究公司Gartner的高级主管分析师托马斯·墨菲（Thomas Murphy）表示，仅仅因为你不一定要根据规范进行测试，并不意味着你不应该为了质量进行测试。 他解释说，今天的测试已从日历事件变为更持续的质量过程。
“There is a fundamental need to be shipping software every day or very frequently, and there is no way that testing can be manual. You don’t have time for that. It needs to be fast,” he said.
“每天或非常频繁地运送软件是一项基本需求，并且测试无法手动进行。 你没有时间。 它需要快速，“他说。
Some ways to speed things up is to capture the requirements and create the tests upfront. Two approaches that really drove the need for automating testing are test-driven development (TDD) and behavior-driven development (BDD). TDD is the idea that you are going to write the test first, then write the code to pass that test, according to Sauce Labs’ Parobek. BDD is where you enable people like the business analyst, product manager or product owners to write tests at the same time developers are developing code.
一些加快速度的方法是捕获需求并预先创建测试。 真正推动自动化测试需求的两种方法是测试驱动开发（TDD）和行为驱动开发（BDD）。 根据Sauce Labs的Parobek的说法，TDD是你要先编写测试，然后编写代码来通过测试。 BDD是让业务分析师，产品经理或产品所有者等人员在开发人员开发代码的同时编写测试。
These approaches have helped teams get software out multiple times a day because they don’t have to wait for days to create the tests and get back results, and it enables them to understand if they make a mistake right away, Parobek explained.
Parobek解释说，这些方法帮助团队每天多次输出软件，因为他们不必等待数天来创建测试并获得结果，这使他们能够立刻了解他们是否犯了错误。
However, if a developer is submitting new code or pull requests to the main branch multiple times a day, it can be hard to keep up with TDD and BDD, making automated testing impossible because there aren’t tests already in place for these changes. In addition, it slows down the process because now you have to go in manually to make sure the code that is being submitted doesn’t break any key existing function, according to Sauce Labs’ Parobek.
但是，如果开发人员每天多次提交新代码或从主分支拉取代码，则可能很难跟上TDD和BDD，因此无法进行自动化测试，因为这些更改尚未进行测试。 此外，根据Sauce Labs的Parobek的说法，它会减慢流程，因为现在你必须手动操作，以确保提交的代码不会破坏任何关键的现有功能。
But Parobek does explain if you write your test correctly and follow best practices, there are ways around this. “As you change your application and as you add new functionality, you do not just create new tests, but you might have to change some existing tests,” he said.
但Parobek确实解释了如果你正确地编写测试并遵循最佳实践，有办法解决这个问题。 “当您更改应用程序并添加新功能时，您不仅要创建新测试，还可能需要更改现有测试，”他说。
Parobek recommends page object modeling as a best practice. It enables users to create tests in a way that is very easy to change when the behavior of the app is changed, he explained. “It enables you to abstract out and keep in one place changes so when the app does change, you are able to change one file that then changes a variety of test cases for you. You don’t have to go into 100 different test cases and change something 100 times. Rather you just change one file that is abstracted through page objects,” he said.
Parobek建议将页面对象建模作为最佳实践。 他解释说，它使用户在更改应用程序时以非常容易更改的方式创建测试。 “它使您能够抽象出来并在一个地方保持变化，因此当应用程序发生变化时，您可以更改一个文件，然后为您更改各种测试用例。 您不必进入100个不同的测试用例并进行100次更改。 相反，你只需要改变一个通过页面对象抽象的文件，“他说。
Another best practice, according to Parobek, is to be smart about locators. Locators enable automated tests to identify different parts of the user interface. A common aspect of locators is IDs. IDs enable tests to identify elements. For example, when an automated test goes in and needs to test a button, if you’ve attached a locator ID to it, the test can recognize the button even if you moved it somewhere else on the page. Other approaches to locators are to use names, CSS selectors, classes, tags links, text and XPath. “Locators are an important part for creating tests that are simpler and easier to maintain,” said Parobek.
根据Parobek的说法，另一个最好的做法就是定位器。 定位器使自动化测试能够识别用户界面的不同部分。 定位器的一个常见方面是ID。 ID使测试能够识别元素。 例如，当自动化测试进入并需要测试按钮时，如果您已将定位器ID附加到该按钮，即使您将按钮移动到页面上的其他位置，测试也可以识别该按钮。 定位器的其他方法是使用名称，CSS选择器，类，标签链接，文本和XPath。 “定位器是创建更简单，更易于维护的测试的重要部分，”Parobek说。
In order to successfully use locators, Parobek thinks it is imperative that the development and QA teams collaborate better. “If QA and development are working closely together, it is easy to build apps that make it easier to test versus development not thinking about testability.”
为了成功使用定位器，Parobek认为开发和QA团队必须更好地协作。 “如果QA和开发部门紧密合作，很容易构建应用程序，使测试与开发更容易，防止开发人员不考虑可测试性。”
No matter how much you end up being able to automate, Black explained in order to be successful at it, you will still always have to go back to the basics. If you become too aspirational with automation and have too many failed attempts, it can reduce management’s appetitive for wanting to invest. “You need to have a plan. You need to have an architecture,” Black said. “The plan needs to include a business case so you can prove to management it is not just throwing money into a bright shiny object.”
无论你最终能够自动化多少，布莱克解释说，为了取得成功，你仍然需要回到基础。 如果您对自动化过于渴望并且尝试失败太多，那么它可能会降低管理层对于想要投资的兴趣。 “你需要有一个计划。 你需要有一个架构，“布莱克说。 “该计划需要包括一个商业案例，这样你就可以向管理层证明，这不是把钱扔进大海。”
“It’s the boring basics. Attention to the business case. Attention to the architecture. Take it step by step and course correct as you go,” Black added.
“这是无聊的基础知识。 关注商业案例。 注意架构。 当你做的时候，一步一步地做，并把它当作正确的方法，“布莱克补充道。
The promise of artificial intelligence in automated testing 人工智能在自动化测试中的承诺
As artificial intelligence (AI) advances, we are seeing it be implemented in more tools and technologies as a way to improve user experience provide business value. But when it comes to test automation, the promise of AI is more inspirational than operational, RBCS’ Black explained.
随着人工智能（AI）的发展，我们看到它在更多工具和技术中实施，作为改善用户体验，提供商业价值的一种方式。 但是，当谈到测试自动化时，人工智能的承诺比操作更具启发性，RBCS的Black解释道。
“If you go to conferences, you will hear about people wanting to use it, and tool vendors making claims that they are able to deliver on it. But at this point, I have not had a client tell me or show me a successful implementation of test automation that relies on AI in a significant way,” he said. “What is happening now is that tool vendors are sensing that this is going to be the next hot thing and are jumping on that AI train. It is not a realized promise yet.”
“如果你去参加会议，你会听到有人想要使用它，工具供应商声称他们能够提供它。 但是在这一点上，我还没有客户告诉我或者向我展示了一个以显着方式依赖AI的测试自动化的成功实施，“他说。 “现在发生的事情是，工具供应商感觉到这将是下一个热门的事情，并且正在跳上那辆AI列车。 这还不是一个实现的承诺。“
When you think about AI, you think about a sentient element figuring things out automatically, according to Gartner’s Murphy, when in reality it tends to be some repeated pattern of learning something to be predictive or learning from past experiences. In order to learn from past experiences, you need a lot of data to feed into your machine learning algorithm. Murphy explained AI is still new and a lot of the test information that companies have today is very fragmented, so when you hear companies talk about AI in regards to test automation it tends to be under-delivering or over-promising.
根据Gartner的Murphy的说法，当你考虑人工智能时，你会想到一个有意识的元素来自动地解决问题，而实际上它往往是一些重复的模式，学习某些事物来预测或从过去的经验中学习。 为了从过去的经验中学习，您需要将大量数据提供给您的机器学习算法。 Murphy解释说AI仍然是新的，公司今天的许多测试信息非常分散，所以当你听到公司在测试自动化方面谈论人工智能时，它往往是交付不足或过于乐观。
Vendors that say they are offering an AI-oriented test automation tool are often just performing model-based testing, according to Murphy. Model-based testing is an approach where tests are automatically generated from models. The closest thing we have out there to an AI-based test automation tool are image-based recognition solutions that understand if things are broken, and can show when it happened and where through visual validation, Murphy explained.
Murphy表示，那些表示他们正在提供面向AI的测试自动化工具的供应商，通常只是在进行基于模型的测试。 基于模型的测试是一种从模型自动生成测试的方法。 我们最接近基于AI的测试自动化工具的是基于图像的识别解决方案，它可以了解事情是否被破坏，并且可以显示它何时发生以及哪里通过视觉验证，Murphy解释说。
However, Black does see AI having potential within the test automation space in the future; he just warns businesses against investing in any technologies too soon. Areas where Black sees the most potential for AI include false positives, and flaky tests.
但是，Black确实认为人工智能在未来的测试自动化领域具有潜力; 他只是警告企业不要过早投资任何技术。 Black认为AI最具潜力的领域包括误报和不稳定测试。
False positives happen when a test returns a failed result, but it turns out the software is actually working correctly. A human being is able to recognize this when they look further into correcting the result. Black sees AI being used to apply human reasoning and differentiate the correct versus incorrect behavior.
当测试返回失败的结果时会发生误报，但事实证明软件实际上正常工作。 当人们进一步观察结果时，人们能够识别出这一点。 Black认为AI用于应用人为推理，并区分正确行为与不正确行为。
Flaky tests happen when a test fails once, but passes when the test runs again. This unpredictable result is due to the variation of the system architecture, the test architecture, the tool, or the test automation, according to Black. He sees AI being used to handle validation issues like this by bringing a more sophisticated sense of what fit for use means to the testing efforts.
当测试失败一次时会发生不稳定测试，但是当测试再次运行时通过了。 Black表示，这种不可预测的结果是由于系统架构，测试架构，工具或测试自动化的变化导致的。 他认为人工智能被用来处理这样的验证问题，通过更加复杂的方式来理解测试工作的适用性。
Kevin Surace, CEO of Appvance.ai, sees AI being applied to test automation, but in different levels. Surace said there are 5 levels of AI that can be applied to test automation:
Appvance.ai首席执行官Kevin Surace认为，人工智能应用于测试自动化，但是在不同层面。 Surace表示，有5个级别的AI可用于测试自动化：
- Scripting/coding 脚本/编码
- “Codeless” capture/playback “无代码”捕获/回放
- Machine learning: self-healing human-created scripts and money bots 机器学习：自我修复人类创造的脚本和金钱机器人
- Machine learning: Near full automation with auto-generated smart scripts 机器学习：使用自动生成的智能脚本实现全自动化
- Machine learning full automation: auto-generated smart scripts with validation 机器学习全自动化：自动生成的智能脚本和验证
When deciding on AI-driven testing, Surace explained the most important qualification is to learn what type of level of AI a vendor is offering. According to Surace, many vendors have offerings at levels one and two, but there are very few vendors that can actually promise levels three and above.
在决定AI驱动的测试时，Surace解释说，最重要的资格是了解供应商提供的AI级别。 根据Surace的说法，许多供应商都提供一级和二级产品，但很少有供应商能够真正提供三级及以上级别。
In the future, Parasoft’s Lambert expects humans will just be looking at the results of test automation with the machine actually doing the testing in an autonomous way. But for now, the real value of AI and machine learning will be used to augment human work and spot patterns and relationships in the data in order to guide the creation and execution of tests, he explained.
在未来，Parasoft的Lambert希望人们只关注测试自动化的结果，而机器实际上是以自主的方式进行测试。 但就目前而言，人工智能和机器学习的真正价值将用于增强人类工作，并在数据中发现模式和关系，以指导测试的创建和执行，他解释说。
Still, Black warns to enter AI for test automation with caution. “Organizations that want to try to use AI-based test automation at this point in time should be extremely careful and extremely conservative in how they pilot that and how they roll that out. They need to remember that the tools are going to evolve dramatically over the next decade, and making hard, fast and difficult to change large investments in automation may not be a wise thing in the long term,” he said.
尽管如此，布莱克仍警告谨慎进入测试自动化的AI。 “想要在这个时间点尝试使用基于AI的测试自动化的组织，应该非常小心并且非常保守地进行试验以及如何实现这一目标。 他们需要记住，这些工具将在未来十年内发生巨大变化，从长远来看，努力，快速和艰难地改变大规模的自动化投资可能不是一件明智的事情，“他说。
Manual practices remain 手动操作保留
Despite the efforts to automate as much as possible, things for the time being will still require a human touch.
尽管尽可能地为自动化多做努力，但目前的事情仍然需要人工操作。
According to Rex Black, president of the Rex Black Consulting Services (RBCS), a hardware and software testing and quality assurance consultancy, you can break testing down into two overlapping categories: 1. Verification, where a test makes sure the software works as specified; and 2. Validation tests, where you make sure tests are fit for use. For now, Black believes validation will remain manual because it is very hard to do in an automated fashion. For example, he explained, if you developed a video game, you can’t automate for things like: Is it fun? Is it engaged? Is it sticky? Do people want to come back and keep playing it?
根据Rex Black咨询服务（RBCS）总裁Rex Black的说法，这是一个硬件和软件测试和质量保证咨询公司，您可以将测试分解为两个重叠的类别：1。验证，测试确保软件按指定的方式工作; 2.验证测试，确保测试适合使用。 目前，Black认为验证将保持手动，因为它很难以自动化方式完成。 例如，他解释说，如果你开发了一款视频游戏，就无法实现以下方面的自动化：它有趣吗？ 操作困难了吗？ 有用户黏性吗？ 人们想回来继续玩吗？
“At this point, automation tools are really about verifying that the software works in some specified way. The test says what is suppose to happen and checks to see if it happens. There is always going to be some validation that will need to be done either by people,” he said.
“此时，自动化工具实际上是在验证软件是否以某种特定方式工作。 测试表明会发生什么，并检查是否发生。 总是会有人需要做一些验证，“他说。
Lubos Parobek, vice president of product for the testing company Sauce Labs explained that even if we get to a point where everything is automated in the long-term future, you will still always want a business stakeholder to take a final look and do a sanity check that everything works as expected to a human.
测试公司Sauce Labs的产品副总裁Lubos Parobek解释说，即使我们在长期未来达到一切自动化的程度，您仍然总是希望业务利益相关者能够最终审视，并做到理智检查，确保一切是否符合人类的预期。
“Getting a complete view of customer experience isn’t just about validating user scenarios, doing click-counts and sophisticated ‘image analysis’ to make sure the look and feel is consistent — it’s about making sure the user is engaged and enjoying the experience. This inherently requires human intuition and cannot be fully automated,” added Mark Lambert, vice president of products for automated software testing company Parasoft.
“全面了解客户体验不仅仅是验证用户场景，进行点击计数和复杂的'图像分析'，以确保外观和感觉一致 - 这是为了确保用户参与并享受体验。 这本身就需要人类的直觉，不能完全自动化，“自动软件测试公司Parasoft产品副总裁Mark Lambert补充道。
Robotic process automation 机器人过程自动化
Test automation vendors are flocking to this idea of robotic process automation (RPA). RPA is a business process automation approach used to cut costs, reduce errors and speed up processes, so what does this have to do with test automation?
测试自动化供应商正在涌向机器人过程自动化（RPA）这一想法。 RPA是一种业务流程自动化方法，用于降低成本，减少错误和加快流程，那么这与测试自动化有什么关系呢？
According to Thomas Murphy, senior director analyst at Gartner, RPA and test automation technologies have a high degree of overlap. “Essentially both are designed to replicate a human user performing a sequence of steps.”
根据Gartner高级主管分析师Thomas Murphy的说法，RPA和测试自动化技术具有高度重叠性。 “基本上两者都旨在复制执行一系列的人类用户操作。”
Anthony Edwards, CTO of the test automation company Eggplant, explained that on a technical level, test automation is about automating user journeys across an app and verifying that what is supposed to happen, happens. RPA aims to do just that. “So at a technical level they are actually the exact same thing, it’s simply the higher level intent and purpose that is different. But if you look at a script that automates a user journey there is no way to tell if it has been created for ‘testing’ or for ‘RPA’ just by looking at it,” said Edwards. “The difference for some people would be that testing focuses on a single application whereas RPA typically works across several systems integrated together.”
测试自动化公司Eggplant的首席技术官Anthony Edwards解释说，在技术层面，测试自动化是关于在应用程序中自动化用户旅程并验证应该发生的事情。 RPA旨在做到这一点。 “因此，在技术层面上，它们实际上完全相同，只是更高层次的意图和目的是不同的。 但是，如果你看一个自动化用户旅程的脚本，就无法通过查看它来判断它是为“测试”或“RPA”而创建的，“爱德华兹说。 “一些人的不同之处在于测试侧重于单个应用程序，而RPA通常可以在多个集成在一起的系统中运行。”
Over the next couple of years, Gartner’s Murphy predicts we will see more test automation vendors entering this space as a new way to capitalize on market opportunity. “By moving into the RPA market, they are expanding their footprint and audience of people they go after to help them,” he said.
在接下来的几年里，Gartner的Murphy预测，我们将看到更多的测试自动化供应商进入这个领域，作为一种利用市场机会的新方法。 他说：“通过进入RPA市场，他们正在扩大他们的足迹以及帮助他们追逐的人群。”
This move is especially important as more businesses move toward open-source technologies for their testing solutions.
随着越来越多的企业转向采用开源技术的测试解决方案，这一举措尤为重要。
Rex Black, president of the Rex Black Consulting Services (RBCS), a hardware and software testing and quality assurance consultancy, sees the test automation space moving towards open source because of cost. “It’s easier to get approval for a test automation project if there isn’t a significant up-front investment in a tool purchase, especially if the test automation project is seen as risky. Related to that aspect of risk is that so many open-source test automation tools have been successful over recent years, so the perceived risk of going with an open-source tool is lower than it used to be,” he said.
Rex Black咨询服务公司（RBCS）总裁Rex Black认为，由于成本原因，测试自动化领域正朝着开源方向发展。 “如果在购买工具时没有大量的前期投资，那么获得测试自动化项目的批准会更容易，特别是如果测试自动化项目被认为是有风险的话。 与风险这一方面相关的是，近年来有如此多的开源测试自动化工具取得了成功，因此使用开源工具的风险低于以往，“他说。
关于作者
About Christina Cardoza
Christina Cardoza is the News Editor of SD Times. She is responsible for the oversight of the daily news published to the website as well as the company's weekly newsletter, News on Monday. She covers agile, DevOps, AI, machine learning, mixed reality and software security. She is an undeniable nerd who loves Marvel comics and Star Wars. On Follow her on Twitter at @chriscatdoza!
Christina Cardoza是SD Times的新闻编辑。 她负责监督发布到网站的每日新闻以及该公司的每周时事通讯周一的新闻。 她介绍了敏捷，DevOps，AI，机器学习，混合现实和软件安全。 她是一个不可否认的书呆子，喜欢漫威漫画和星球大战。 在Twitter上关注她@chriscatdoza！
原链接
https://sdtimes.com/test/pushing-automated-testing-to-its-limits/
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