How can the existing unit test possibly fail by adding another test?

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existing
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Somehow this existing test fails on the unit testing and the one above is passing. (VERY WEIRD), Is it possible for everything that exists to have a definition? ,EDIT: somehow I get the error from the existing method and the stacktrace shows I'm getting an error on here:

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For example, it is hard to reason about the following code, which depends on a globally accessible property:,However, sometimes new is absolutely harmless: for example, it is OK to create simple entity objects:,Unit testing is a method that instantiates a small part of our code and verifies its behavior independently from other parts of the project.

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If you write code that stuffs things into a database or that reads a file from disk, you have not written a unit test.  Unit tests don’t deal with their environment and with external systems to the codebase.  If it you’ve written something that can fail when run on a machine without the “proper setup,” you haven’t written a unit test.,Fortunately, you can do better.  Since one or two other people have tried unit testing before you picked it up, some enterprising folks built frameworks to make it easier.  Let’s take a look at how to do that.,I’m sure you can pick out the flaw in this approach.  While you might enjoy your newfound ability to verify that 5 + 6 does, indeed, return 11, you probably don’t want to create and run a new console project for each unit test that you write.

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Another test-support module with a very different flavor.,The standard output and standard error streams are buffered during the test run. Output during a passing test is discarded. Output is echoed normally on test fail or error and is added to the failure messages.,Signals a test failure unconditionally, with msg or None for the error message.

import unittest

class TestStringMethods(unittest.TestCase):

   def test_upper(self):
   self.assertEqual('foo'.upper(), 'FOO')

def test_isupper(self):
   self.assertTrue('FOO'.isupper())
self.assertFalse('Foo'.isupper())

def test_split(self):
   s = 'hello world'
self.assertEqual(s.split(), ['hello', 'world'])
# check that s.split fails when the separator is not a string
with self.assertRaises(TypeError):
   s.split(2)

if __name__ == '__main__':
   unittest.main()
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After covering those fundamentals, we explain the difference between unit tests and another common and valuable type of testing, integration tests. We then explore the fact that not all code is created equal: some pieces of code might be easy to unit test, while others might be downright untestable. Understanding that difference is crucial: you can’t achieve good code coverage without writing testable code.,The line between unit tests and integration tests can be hard to see for beginners. Both unit tests and integration tests can be written using the same tools. Also, both forms of testing consist of writing “examples” of interactions to a piece of code. They might even look very alike, or even identical. So, what’s the difference?,When it comes to unit testing, you should prevent them from becoming too coupled to the internals of the code they’re testing. That way, they’re more resilient in the face of change, allowing the developers to change internal implementation and refactor when needed while providing valuable feedback and a safety net.

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In computer programming, unit testing is a software testing method by which individual units of source code—sets of one or more computer program modules together with associated control data, usage procedures, and operating procedures—are tested to determine whether they are fit for use.[1] ,Unit testing is also critical to the concept of Emergent Design. As emergent design is heavily dependent upon refactoring, unit tests are an integral component.[17] ,Unit testing frameworks are most often third-party products that are not distributed as part of the compiler suite. They help simplify the process of unit testing, having been developed for a wide variety of languages.

import static org.junit.Assert.assertEquals;

import org.junit.Test;

public class TestAdder {

   @Test
   public void testSumPositiveNumbersOneAndOne() {
      Adder adder = new AdderImpl();
      assertEquals(2, adder.add(1, 1));
   }

   // can it add the positive numbers 1 and 2?
   @Test
   public void testSumPositiveNumbersOneAndTwo() {
      Adder adder = new AdderImpl();
      assertEquals(3, adder.add(1, 2));
   }

   // can it add the positive numbers 2 and 2?
   @Test
   public void testSumPositiveNumbersTwoAndTwo() {
      Adder adder = new AdderImpl();
      assertEquals(4, adder.add(2, 2));
   }

   // is zero neutral?
   @Test
   public void testSumZeroNeutral() {
      Adder adder = new AdderImpl();
      assertEquals(0, adder.add(0, 0));
   }

   // can it add the negative numbers -1 and -2?
   @Test
   public void testSumNegativeNumbers() {
      Adder adder = new AdderImpl();
      assertEquals(-3, adder.add(-1, -2));
   }

   // can it add a positive and a negative?
   @Test
   public void testSumPositiveAndNegative() {
      Adder adder = new AdderImpl();
      assertEquals(0, adder.add(-1, 1));
   }

   // how about larger numbers?
   @Test
   public void testSumLargeNumbers() {
      Adder adder = new AdderImpl();
      assertEquals(2222, adder.add(1234, 988));
   }
}
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In computer programming, unit testing is a software testing method by which individual units of source code are tested to determine whether they are fit for use. A unit is the smallest possible testable software component. Usually, it performs a single cohesive function. A unit is small, so it is easier to design, execute, record, and analyze test results for than larger chunks of code are. Defects revealed by a unit test are easy to locate and relatively easy to repair.,Issues are found at an early stage. Since unit testing is carried out by developers who test individual code before integration, issues can be found very early and can be resolved then and there without impacting the other pieces of the code. This includes both bugs in the programmer’s implementation and flaws or missing parts of the specification for the unit.,Unit testing provides documentation of the system. Developers looking to learn what functionality is provided by a unit and how to use it can look at the unit tests to gain a basic understanding of the unit’s interface (API).

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