下面是对每一个的描述，然后是真实世界的样本。

Dummy - just bogus values to satisfy the API. Example: If you're testing a method of a class which requires many mandatory parameters in a constructor which have no effect on your test, then you may create dummy objects for the purpose of creating new instances of a class. Fake - create a test implementation of a class which may have a dependency on some external infrastructure. (It's good practice that your unit test does NOT actually interact with external infrastructure.) Example: Create fake implementation for accessing a database, replace it with in-memory collection. Stub - override methods to return hard-coded values, also referred to as state-based. Example: Your test class depends on a method Calculate() taking 5 minutes to complete. Rather than wait for 5 minutes you can replace its real implementation with stub that returns hard-coded values; taking only a small fraction of the time. Mock - very similar to Stub but interaction-based rather than state-based. This means you don't expect from Mock to return some value, but to assume that specific order of method calls are made. Example: You're testing a user registration class. After calling Save, it should call SendConfirmationEmail.

存根和Mock实际上是Mock的子类型，两者都交换了实际实现和测试实现，但出于不同的、特定的原因。

在我的回答中，我使用了python示例来说明差异。

Stub - Stubbing is a software development technique used to implement methods of classes early in the development life-cycle. They are used commonly as placeholders for implementation of a known interface, where the interface is finalized or known but the implementation is not yet known or finalized. You begin with stubs, which simply means that you only write the definition of a function down and leave the actual code for later. The advantage is that you won't forget methods and you can continue to think about your design while seeing it in code. You can also have your stub return a static response so that the response can be used by other parts of your code immediately. Stub objects provide a valid response, but it's static no matter what input you pass in, you'll always get the same response:

class Foo(object):
    def bar1(self):
        pass

    def bar2(self):
        #or ...
        raise NotImplementedError

    def bar3(self):
        #or return dummy data
        return "Dummy Data"

模拟对象用于模拟测试用例，它们验证在这些对象上调用了某些方法。模拟对象是以可控的方式模拟真实对象行为的模拟对象。您通常创建一个模拟对象来测试其他对象的行为。mock让我们模拟对于单元测试来说不可用或太笨重的资源。

mymodule.py:

import os
import os.path

def rm(filename):
    if os.path.isfile(filename):
        os.remove(filename)

test.py:

from mymodule import rm
import mock
import unittest

class RmTestCase(unittest.TestCase):
    @mock.patch('mymodule.os')
    def test_rm(self, mock_os):
        rm("any path")
        # test that rm called os.remove with the right parameters
        mock_os.remove.assert_called_with("any path")

if __name__ == '__main__':
    unittest.main()

这是一个非常基本的示例，它只运行rm并断言调用它的参数。您可以对对象使用mock，而不仅仅是这里所示的函数，您还可以返回一个值，这样模拟对象就可以用来替换存根进行测试。

更多关于unittest的信息。模拟，注意python 2。X mock不包含在unittest中，但它是一个可下载的模块，可以通过PIP (PIP install mock)下载。

我还读过Roy Osherove写的《单元测试的艺术》，我认为如果有一本类似的书是用Python和Python示例编写的，那就太棒了。如果有人知道这样的书，请分享。欢呼:)

我偶然看到了《小嘲笑者鲍勃叔叔》的一篇有趣的文章。它以一种非常容易理解的方式解释了所有的术语，因此对初学者很有用。Martin fowler的文章很难读，尤其是对于像我这样的初学者。

我认为他们之间最重要的区别是他们的意图。

让我试着用WHY stub和WHY mock来解释它

假设我正在为我的mac twitter客户端的公共时间轴控制器编写测试代码

下面是测试示例代码

twitter_api.stub(:public_timeline).and_return(public_timeline_array)
client_ui.should_receive(:insert_timeline_above).with(public_timeline_array)
controller.refresh_public_timeline

STUB:到twitter API的网络连接非常慢，这使得我的测试很慢。我知道它将返回时间轴，所以我制作了一个模拟HTTP twitter API的存根，这样我的测试将非常快地运行它，即使我离线也可以运行测试。 MOCK:我还没有写任何我的UI方法，我不确定我需要为我的UI对象写什么方法。我希望通过编写测试代码了解我的控制器如何与我的ui对象协作。

通过编写mock，您可以通过验证期望是否满足来发现对象的协作关系，而stub仅模拟对象的行为。

如果您想了解更多关于模拟的知识，我建议您阅读这篇文章:http://jmock.org/oopsla2004.pdf

Mock只是测试行为，确保调用了特定的方法。 Stub是特定对象的可测试版本(本质上)。

你说的苹果方式是什么意思?

看了上面所有的解释，让我试着总结一下:

Stub:让测试运行的一段虚拟代码，但您并不关心它会发生什么。替代实际工作代码。 Mock:在测试中验证是否正确调用的一段虚拟代码。替代实际工作代码。 间谍:一段虚拟代码，用于拦截和验证对实际工作代码的某些调用，从而避免替换所有实际代码。