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
我喜欢Roy Osherove的解释。
创建的每个类或对象都是Fake。如果您验证它是一个Mock 反对它的呼声。否则就是存根。
其他回答
从论文模拟角色,而不是对象,由jMock的开发人员:
存根是返回罐装的产品代码的虚拟实现 结果。Mock对象充当存根,但也包括到的断言 测量目标对象与其邻居的交互作用。
所以,主要的区别是:
在存根上设置的期望通常是通用的,而在mock上设置的期望可能更“聪明”(例如,在第一次调用时返回this,在第二次调用时返回this等)。 存根主要用于设置SUT的间接输入,而mock可用于测试SUT的间接输入和间接输出。
综上所述,同时也试图驱散福勒文章标题中的困惑:mock是存根,但它们不仅仅是存根。
有很多很棒的答案,我喜欢这个,所以我把它做成了一个表格。
Dummy | Stub | Mock | Fake | |
---|---|---|---|---|
API | O | O | O | O |
States | X | O | O | O |
Values | X | X | O | O |
Behavior | X | X | X | O |
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
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:)
以下是我的理解……
如果您在本地创建测试对象并将其提供给本地服务,则使用的是模拟对象。 这将为您在本地服务中实现的方法提供测试。 它用于验证行为 当您从真正的服务提供者获得测试数据时(尽管是从接口的测试版本获得对象的测试版本),您是在使用存根 存根可以有逻辑来接受特定的输入并给出相应的输出来帮助您执行状态验证…
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