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:)

Stubs vs. Mocks Stubs provide specific answers to methods calls ex: myStubbedService.getValues() just return a String needed by the code under test used by code under test to isolate it cannot fail test ex: myStubbedService.getValues() just returns the stubbed value often implement abstract methods Mocks "superset" of stubs; can assert that certain methods are called ex: verify that myMockedService.getValues() is called only once used to test behaviour of code under test can fail test ex: verify that myMockedService.getValues() was called once; verification fails, because myMockedService.getValues() was not called by my tested code often mocks interfaces

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:)

Mock——Mock拦截对一个方法或函数的调用(或者像模拟类那样的一组方法和函数)。它不是该方法或函数的替代品。在那次拦截中，mock可以做任何它想做的事情，比如记录输入和输出，决定短路调用，更改返回值，等等。

存根——存根是一个有效的方法或函数(或一组方法和函数，就像存根类一样)的完整工作实现，它与它存根的方法、函数或一组方法和函数具有相同的接口/签名。stub实现通常只会做在单元测试上下文中可以接受的事情，这意味着它不会做IO，同时模仿它要stub的东西的行为。

Stub

我相信最大的区别是您已经编写了带有预定行为的存根。所以你会有一个实现依赖的类(很可能是抽象类或接口)，你是为了测试目的而伪造的，方法只是用设置的响应来存根。它们不会做任何花哨的事情，而且您应该已经在测试之外为它编写了存根代码。

Mock

模拟是测试的一部分，你必须根据你的期望来设置。mock并不是预先设定好的，所以您可以在测试中使用它。模拟在某种程度上是在运行时确定的，因为设置期望的代码必须在它们执行任何操作之前运行。

mock和stub的区别

使用模拟编写的测试通常遵循初始化->设置期望->练习->验证模式进行测试。而预先编写的存根将遵循初始化->练习->验证。

mock和stub之间的相似性

这两种方法的目的都是为了消除对类或函数的所有依赖项的测试，从而使您的测试在试图证明的内容方面更加集中和简单。

A fake is a generic term that can be used to describe either a stub or a mock object (handwritten or otherwise), because they both look like the real object. Whether a fake is a stub or a mock depends on how it’s used in the current test. If it’s used to check an interaction (asserted against), it’s a mock object. Otherwise, it’s a stub. Fakes makes sure test runs smoothly. It means that reader of your future test will understand what will be the behavior of the fake object, without needing to read its source code (without needing to depend on external resource). What does test run smoothly mean? Forexample in below code: public void Analyze(string filename) { if(filename.Length<8) { try { errorService.LogError("long file entered named:" + filename); } catch (Exception e) { mailService.SendEMail("admin@hotmail.com", "ErrorOnWebService", "someerror"); } } } You want to test mailService.SendEMail() method, to do that you need to simulate an Exception in you test method, so you just need to create a Fake Stub errorService class to simulate that result, then your test code will be able to test mailService.SendEMail() method. As you see you need to simulate a result which is from an another External Dependency ErrorService class.