/jan 4, 2015

Automated Unit Test Generation for Java

By Asankhaya Sharma

Unit testing is an important aspect of software development. Having a proper test suite for your project can help detect bugs early and prevent regressions. Wouldn't it be great if we could generate unit test cases automatically? Well, it is certainly possible and I will explain in this article how you can do so for Java.

Recently, I had a chance to look at unit test case generation for Java. I had forked an old cross platform serialization library wox and it did not come with a test suite. I had to make a few changes and fix some bugs in the library to make it work with the current version of Java platform. I wanted to ensure that the changes I made did not break any existing functionality. Since the wox library did not come with its own set of test cases it was difficult to check that no regression bugs were introduced.

After searching online, I found an automated test suite generation framework for Java - EvoSuite. The EvoSuite framework automatically generates test cases for Java classes based on maximizing a coverage criteria, like branch coverage. I used their standalone jar to add a test suite to the wox library. It was surprisingly easy to set up and use.

In order to generate the test suite we use the following command:

java -jar evosuite.jar -generateTests <target> [options]

The \ can be either a jar file or a folder containing your class files. If no \ is specified, the command would generate the test cases in a folder named "evosuite-tests" in the current directory.

The test cases generated use JUnit and can be run separately from an IDE as well.

The [options] control various parameters including coverage criteria, the default criteria is branch coverage. Thus the generated tests cover all the branches in the methods. If you are using some external library then make sure that it is available in the class path otherwise EvoSuite will not be able to create test cases with objects that are defined in that library. These external libraries are needed by EvoSuite so it can call the appropriate constructors for those objects during generation.

For test case generation, EvoSuite has a bunch of different strategies including search-based and constraint-based algorithms.

  • Search Based Test Generation : Uses a genetic algorithm to evolve the population of candidate test cases that satisfy a particular fitness function.

  • Constraint Based Test Generation : Uses symbolic execution to generate constraints and solve those constraints to explore different paths in the program.

Their ASE 2011 paper explains both of the above techniques and how they can be combined and used together.

In terms of the quality of the automated generated test cases, it seems to do a good job of capturing the current behavior of the methods while providing good branch coverage. As an example, consider the following method from the wox.serial.Util class :

/**
* Returns true if the class which name is passed as parameter is <i>stringable</i>.
* In other words, returns true if objects of the class can go easily to a string
* representation.
* @param name The name of the class to test.
* @return True if the class is stringable. False otherwise.
*/
public static boolean stringable(String name) {
  try {
    Class realDataType = (Class)TypeMapping.mapWOXToJava.get(name);
    //if the data type was found in the mapWOXToJava then it is "stringable"
    if (realDataType!=null){
      return true;
    }
    else{
      return false;
    }
    } catch(Exception e) {
      return false;
    }
  }

The stringable method has two branches that correspond to whether the input name can be converted to a string by the mapWOXToJava.get method. EvoSuite generates the following two test cases for this method. test02 covers the branch where the conditional is true whole test03 covers the else branch. Also note that it is automatically able to create the inputs for name argument that drive the execution to the different branches.

  //Test case number: 2
  /*
  * 1 covered goal:
  * 1 wox.serial.Util.stringable(Ljava/lang/String;)Z: I10 Branch 21 IFNULL L125 - false
  */

  @Test
  public void test02()  throws Throwable  {
    boolean boolean0 = Util.stringable("charWrapper");
    assertEquals(true, boolean0);
  }

  //Test case number: 3
  /*
  * 1 covered goal:
  * 1 wox.serial.Util.stringable(Ljava/lang/String;)Z: I10 Branch 21 IFNULL L125 - true
  */

  @Test
  public void test03()  throws Throwable  {
    boolean boolean0 = Util.stringable("2p8f2V@rzS");
    assertEquals(false, boolean0);
  }

You can have a look at the entire test suite generated for the wox library at the GitHub repo. For the purpose of creating a regression test suite for a library that did not have one, it seems to be quite effective. Now, if I make some changes in the wox library I can run the tests again and check if it leads to any test failures.

There are a couple considerations to keep in mind when using automated test generation. First, in general, automated test cases may not be as good as hand written ones. Another potential issue is the evolution of the test suite. Generating new tests with EvoSuite for each new EvoSuite release may not be the right thing to do.

Nevertheless the automated test suite can be used as a base for writing your own more comprehensive test cases, which is what I plan to do with the wox library.

There are several other tools (under active development) for Java that also produce automated unit test cases. I haven't had a chance to use them yet but I list them here for reference - CATG, Randoop and Symbolic Pathfinder. An experience report, titled EvoSuite at the Second Unit Testing Tool Competition provides more details on using EvoSuite and how it compares with other similar tools.

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By Asankhaya Sharma

Dr. Asankhaya Sharma is the Director of Software Engineering at Veracode. Asankhaya is a cyber security expert and technology leader with over a decade of experience in creating security products for industry, academia and open-source community. He is passionate about building high performing teams and taking innovative products to market. He is also an Adjunct Professor at the Singapore Institute of Technology.