问题

作为测试人员,我们应该或不应该我们讨论人工智能工具如chatGPT吗?

  • 2023年5月10日
  • 5回复
  • 130的浏览量
anuvip
Userlevel 6
徽章 + 2
  • anuvip
  • 0.8跨声速
  • 20个回复

ChatGPT热门话题,可以为测试活动提供一些好处,但它在加快测试过程的有效性或生成测试用例将取决于具体的用例和输入数据的质量提供给它。当人们不想错过火车,但他们必须非常清楚,他们应该如何使用人工智能。在我看来,ChatGPT可以帮助测试在以下方面:

  1. 测试数据生成:ChatGPT可以用于生成合成测试数据基于特定场景或需求。例如,它可以生成测试数据,模拟特定的用户或系统的交互反应来验证一个软件应用程序的功能。188金宝搏官网登录app

  2. 测试用例生成:ChatGPT可用于生成测试用例根据特定需求或测试场景。然而,这种方法的有效性将取决于输入数据的质量提供给模型和测试用例所需的详细级别。

  3. 自动化测试脚本:ChatGPT可用于自动化测试脚本重复的任务,如创建测试数据或验证。这可以帮助加快测试过程,提高测试团队的效率。

在上面列出的好处,重要的是要注意,虽然ChatGPT可以帮助在测试活动中,它不是一个替代人类的测试人员。人们会开始认为这可以替代他们,他们的工作。然而,它仍然是人类需要测试人员可以验证结果生成的模型并提供上下文和领域知识,可能不会被模型。

你的想法是什么?

质量的主张,一些
The talk of the town, ChatGPT, can provide some benefits for testing activities, but its effectiveness in speeding up the testing process or generating test cases will depend on the specific use case and the quality of the input data provided to it. While people do not want to miss the train, but they have to very clear where and how they should use AI. In my\u00a0opinion,\u00a0ChatGPT can help in testing in following ways:<\/p>
  1. \t

    Test data generation: ChatGPT can be used to generate synthetic test data based on specific scenarios or requirements. For instance, it can generate test data that simulates specific user interactions or system responses to validate the functionality of a software application.<\/p>\t<\/li>\t

  2. \t

    Test case generation: ChatGPT can be used to generate test cases based on specific requirements or test scenarios. However, the effectiveness of this approach will depend on the quality of the input data provided to the model and the level of detail required for the test cases.<\/p>\t<\/li>\t

  3. \t

    Test script automation: ChatGPT can be used to automate test scripts for repetitive tasks, such as test data creation or validation. This can help speed up the testing process and improve the efficiency of the testing team.<\/p>\t<\/li><\/ol>

    Having listed the above benefits, It is important to note that while ChatGPT can help in testing activities, it is not a replacement for human testers. People will start thinking that this can replace them and take their jobs. However, It is still necessary to have human testers who can validate the results generated by the model and provide context and domain knowledge that may not be captured by the model.<\/p>

    \u00a0<\/p>

    What are your thoughts?<\/p>

    \u00a0<\/p>

    \u00a0<\/p>

    \u00a0<\/p>","quoteUsername":"anuvip","translations":{"Common":{"like":"Like","unlike":"Unlike"},"Forum":{"Quote":"Quote & Reply","Share":"Share"}}}">

5回复

H
Userlevel 2
徽章

你好一些

之前有几点可能需要考虑将我们的应用程序与Gpt聊天。

1。的数据存储以及它的使用方式,安全方面的数据。

2。聊天Gpt缺乏的功能知识测试,所以我们可能需要培训系统有关

数据。

3所示。我们可能需要检查是否数据生成的聊天Gpt包含任何偏见。

4所示。有时聊天Gpt所产生的数据可能是错的。

Hi Vipin,<\/p>

There are few points which may need to consider before integrating our application with Chat Gpt.<\/p>

1. Where the data is stored and how it is used, security aspect of the data as well.<\/p>

2.Chat Gpt lacks the functional knowledge of testing so we may need to train the system with relevant\u00a0<\/p>

Data.<\/p>

3. We may need to check if the data generated by chat Gpt contains any biases.<\/p>

4. Some times the data generated by chat Gpt might be wrong.<\/p>","quoteUsername":"Harish N","translations":{"Common":{"like":"Like","unlike":"Unlike"},"Forum":{"Quote":"Quote & Reply","Share":"Share"}}}">

一个
Userlevel 5
徽章 + 3

有很多争论隐私与数据捕获刚才应该作为一个考虑因素。私人公司或项目信息共享数据ChatGPT可能因此引起关注

不再担心,一些普遍的用例:

  • TA脚本代码生成
  • 搜索相关的开源TA示例代码的建议
  • 决策表,随机范围建筑,流路径选择有用的测试用例
  • 测试数据生成的随机数据网络
  • 聊天机器人&答案收集(更缩小,具体谷歌搜索替代测试问题)
  • 文本解析和提取使用神经网络类型的理解
  • 收集互联网上可用的基于信息的测试重点建议(给定一个web前端- rest web服务数据库后端,什么是适当的测试执行,哪些性能测试优先级最高)
  • 混沌工程学领域失败的建议
  • 工具的建议和比较
  • 测试用例生成(即上传一组全面的测试步骤与所有公司数据,url等积极的测试用例和要求删除负面测试用例生成的版本)

为内部毫升数据问题并不是一个问题,更多的选择:

  • 缺陷内容生成(也许困难普遍)
  • 缺陷priotity &严重程度选择援助
  • 相关测试用例选择(每释放,缺陷修复等)
  • 接触点,集中& +需求范围,示例代码的其他项目使用类似或相同的被测系统
  • 使用统计测试——频率,ROI的计算,节省时间的估计
  • 测试需求分析-时间、人员、成本估计
  • 趋势分析-失败的被测系统,环境,缺陷测量,开发人员修复测量
  • 预测被测系统改变测试需求(LiveCompare、页面对象模型生成变化影响等)
  • 监控日志解析,分析和预测系统使用,性能趋势每天+时间,比较环境统计数据
  • 报告的改进、数据合并
  • 项目需求和架构分析共性和趋势在一个组织
There\u2019s a lot of debate over the privacy & data capture just now which should be taken as a consideration. Private company data or project info sharing to ChatGPT might therefore cause concern<\/p>
K
Userlevel 1

有很多争论隐私与数据捕获刚才应该作为一个考虑因素。私人公司或项目信息共享数据ChatGPT可能因此引起关注

不再担心,一些普遍的用例:

  • TA脚本代码生成
  • 搜索相关的开源TA示例代码的建议
  • 决策表,随机范围建筑,流路径选择有用的测试用例
  • 测试数据生成的随机数据网络
  • 聊天机器人&答案收集(更缩小,具体谷歌搜索替代测试问题)
  • 文本解析和提取使用神经网络类型的理解
  • 收集互联网上可用的基于信息的测试重点建议(给定一个web前端- rest web服务数据库后端,什么是适当的测试执行,哪些性能测试优先级最高)
  • 混沌工程学领域失败的建议
  • 工具的建议和比较
  • 测试用例生成(即上传一组全面的测试步骤与所有公司数据,url等积极的测试用例和要求删除负面测试用例生成的版本)

为内部毫升数据问题并不是一个问题,更多的选择:

  • 缺陷内容生成(也许困难普遍)
  • 缺陷priotity &严重程度选择援助
  • 相关测试用例选择(每释放,缺陷修复等)
  • 接触点,集中& +需求范围,示例代码的其他项目使用类似或相同的被测系统
  • 使用统计测试——频率,ROI的计算,节省时间的估计
  • 测试需求分析-时间、人员、成本估计
  • 趋势分析-失败的被测系统,环境,缺陷测量,开发人员修复测量
  • 预测被测系统改变测试需求(LiveCompare、页面对象模型生成变化影响等)
  • 监控日志解析,分析和预测系统使用,性能趋势每天+时间,比较环境统计数据
  • 报告的改进、数据合并
  • 项目需求和架构分析共性和趋势在一个组织

这是一个非常全面的列表,谢谢你的分享

库巴地毯
\t

There\u2019s a lot of debate over the privacy & data capture just now which should be taken as a consideration. Private company data or project info sharing to ChatGPT might therefore cause concern<\/p>\t

一个
Userlevel 5
徽章 + 3

可能1000年代的我没有想到太…期待看到这篇文章长&想法别人想出另外的什么!

probably 1000s of bits I didn\u2019t think of too\u2026\u00a0am looking forward to seeing how this post grows & what ideas others come up with in addition!\u00a0\ud83d\ude00<\/p>","quoteUsername":"alex_read","translations":{"Common":{"like":"Like","unlike":"Unlike"},"Forum":{"Quote":"Quote & Reply","Share":"Share"}}}">
年代
Userlevel 4
徽章 + 4

我看到很多浅和不计后果的讨论ChatGPT能做什么为测试人员。

我们需要调查可以用基于ai工具。只是告诉人们“你可以这样做!和THIIIISSS !“不为测试人员或行业。这是不负责任的。

我见过几个示威的人使用ChatGPT生成测试用例和脚本,我看到的是一个热混乱没有批判性思维。是的,ChatGPT可以做一些有趣的事情,但这不是能做他们一致和可靠的。

一个学生最近回应一个练习我给他问ChatGPT编写一个程序,判断一个字符串的日期(提供输出程序的声称产生随机日期)是或不是随机的。提供的程序高高兴兴地和自信ChatGPT非常不适合这项任务,但测试人员没有数学或编程技能必要的意识到。他只是通过程序我断言,它解决了这个问题。

我们不应该鼓励人们的行为。

在缺乏一致性和可靠性的情况下,我认为那些依靠ChatGPT将他们的工作处于危险之中。我将鼓励雇主解雇进攻依赖它,就像如果你发现开发人员将他们的工作外包给其他程序员,并谎称是自己的。

我认为人工智能可以有一个角色。具体来说,ChatGPT可以作为一种有用的即时教程发电机如果你想开始使用特定工具或技术。我也认为它可以用来帮助头脑风暴或培训测试人员。

举例来说,一个好的训练可能会问ChatGPT“三个测试用例是什么打印机?”然后让测试人员审查和解决这个问题的答案(因为ChatGPT的回答将会远远低于专业标准在重要方面)。

或者你可以描述一个特性和要求ChatGPT测试的想法。它会给你明显的——也许——也许两个奇怪的人。但是你需要删除和添加一些其他人。

这是一个专业的规则我已经当我用ChatGPT:我从来没有问我的答案没有当场个人知识和技能评估,因为超过一半的时间,我确实有这样的知识和技能,我看到ChatGPT重要错误输出。

I\u2019m seeing a lot of shallow and reckless talk about what ChatGPT can do for testers.<\/p>

We do need to investigate what can be done with AI-based tools. But just telling people \u201cYOU CAN DO THIS! AND THIIIISSS!\u201d does not serve testers or the industry. It is irresponsible.<\/p>

I have seen several demonstrations of people generating test cases and scripts using ChatGPT and what I\u2019ve seen is a hot mess without much critical thinking. Yes, ChatGPT can do interesting things, but it is not able to do them\u00a0consistently and reliably.<\/p>

A student recently responded to an exercise I gave him by asking ChatGPT to write a program to tell if a\u00a0string of dates (provided as output of a program that purported to produce random dates) were or were not random. The program cheerfully and confidently supplied by ChatGPT was profoundly unsuited to the task, but the tester did not have the mathematical or programming skills necessary to realize that. He just passed the program on to me with the assertion that it solved the problem.<\/p>

We should not be encouraging people to behave that way.<\/em><\/p>

In the absence of consistency and reliability, I would say anyone who relies on ChatGPT is putting their job at risk. I would encourage employers to make it a firing offense to rely on it-- just as it would be if you discovered that developers were outsourcing their work to other programmers and passing it off as their own.<\/p>

I do think AI can have a role.<\/strong> Specifically, ChatGPT can be useful as a sort of instant tutorial generator if you are trying to get started using a particular tool or technology. I also think it can be used to aid in brainstorming or training testers.<\/p>

For instance, a good training exercise might be to ask ChatGPT \u201cwhat are three test cases for a printer?\u201d and then ask a tester to review and fix that answer (because ChatGPT\u2019s answer will be far below a professional standard in important ways).<\/p>

Or you can describe a feature and ask ChatGPT for test ideas. It will give you the obvious ones-- probably-- and maybe a couple of strange ones. But then you need to delete some and add others.<\/p>

Here\u2019s a professional rule I have when I use ChatGPT: I never\u00a0ask it for answers that I do not have the personal knowledge and skill to evaluate on the spot, because more than half the time that I DO have such knowledge and skill, I see important errors in ChatGPT output.<\/p>","quoteUsername":"satisfice","translations":{"Common":{"like":"Like","unlike":"Unlike"},"Forum":{"Quote":"Quote & Reply","Share":"Share"}}}">

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