我读过各种关于测试中模仿和存根的文章,包括Martin Fowler的《Mocks Aren't Stubs》,但我仍然不理解其中的区别。


当前回答

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:)

其他回答

存根用于您在测试中设置的具有预期返回值的方法。 mock用于void方法,这些方法在调用时的Assert中进行验证。

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

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.

非常清楚和实际:

Stub:实现要伪造的类/对象的方法的类或对象,并且总是返回你想要的东西。

JavaScript示例:

var Stub = {
   method_a: function(param_a, param_b){
      return 'This is an static result';
   }
}

Mock:与存根相同,但是它增加了一些逻辑,当一个方法被调用时“验证”,这样你就可以确定某个实现正在调用该方法。

正如@mLevan所说,假设你正在测试一个用户注册类。在调用Save之后,它应该调用SendConfirmationEmail。

一个非常愚蠢的代码

var Mock = {
   calls: {
      method_a: 0
   }

   method_a: function(param_a, param_b){
     this.method_a++; 
     console.log('Mock.method_a its been called!');
   }
}

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:)