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:)

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

如果你把它比作调试:

Stub类似于确保一个方法返回正确的值 Mock实际上就像进入方法，在返回正确值之前确保里面的所有内容都是正确的。

他使用的通用术语是测试替身(想想特技替身)。Test Double是一个通用术语，用于为测试目的替换生产对象的任何情况。杰拉德列出了各种各样的替身:

Dummy objects are passed around but never actually used. Usually they are just used to fill parameter lists. Fake objects actually have working implementations, but usually take some shortcut which makes them not suitable for production (an InMemoryTestDatabase is a good example). Stubs provide canned answers to calls made during the test, usually not responding at all to anything outside what's programmed in for the test. Spies are stubs that also record some information based on how they were called. One form of this might be an email service that records how many messages it was sent(also called Partial Mock). Mocks are pre-programmed with expectations which form a specification of the calls they are expected to receive. They can throw an exception if they receive a call they don't expect and are checked during verification to ensure they got all the calls they were expecting.

源

假设你有一个名为EmployeeService的类，你想测试它，并且它对一个名为EmployeeDao的接口有一个依赖:

public class EmployeeService{
   private EmployeeDao dao;
   public EmployeeService(Dao dao){this.dao = dao;}

   public String getEmployeeName(int id){
     Employee emp = bar.goToDatabaseAndBringTheEmployeeWithId(id);
     return emp != null?emp.getFullName:null;
   }
   //Further state and behavior
}

public interface EmployeeDao{
  Employee goToDatabaseAndBringTheEmployeeWithId(int id);
}

在测试类内部:

public class EmployeeServiceTest{
   EmployeeService service;
   EmployeeDao mockDao = Mockito.mock(EmployeeDao.class);//Line 3

   @Before
   public void setUp(){
     service = new EmployeeService(mockDao);
   }
   //Tests
   //....
}

在上面的测试类的第3行中，我们对mock框架(在本例中是Mockito)说“嘿，Mockito，给我做一个具有EmployeeDao功能的对象。”框架将创建一个对象，它有goToDatabaseAndBringTheEmployeeWithId方法，但实际上没有主体。你的工作就是指导那个mock做什么。这是一个嘲弄。

但是你也可以创建一个实现EmployeeDao接口的类，并在测试类中使用它:

public EmployeeDaoStub implements EmployeeDao{
   public Employee goToDatabaseAndBringTheEmployeeWithId(int id){
      //No trip to DB, just returning a dummy Employee object
      return new Employee("John","Woo","123 Lincoln str");
   }
}

在你的测试类中，这次使用stub而不是mock:

public class EmployeeServiceTest{
   EmployeeService service;
   EmployeeDao daoStub = new EmployeeDaoStub();//Line 3

   @Before
   public void setUp(){
     service = new EmployeeService(daoStub);
   }
   //Tests
   //....
}

因此，为了包装这一切，存根是您(或其他人)专门创建的类，以模仿某些依赖关系，只是为了拥有所需的状态。是的，正如其他人所说，它主要是关于一个状态，而mock通常是由mock框架创建的，您不知道它的内部是什么样子的。但是使用存根，您知道将得到什么类:它是您创建的类。

哦，顺便说一下，如果你的依赖项是一个类而不是一个接口，你可以扩展这个类来创建你的存根。