Generating automated tests from specifications

In most cases, the implementation of automated testing focuses on the automated execution of previously defined test cases. These test cases come in the form of test scripts or use cases that are prepared by test analists or test engineers. Often, before the introduction of automated testing in a project and / or team, these test cases were executed by hand in the past.

However, what if we could also automate the creation of test cases? When applied correctly, this would yield an even more efficient testing process. Furthermore, the number of mistakes in the derivation of test cases would be reduced to 0 (given that the test case generator is functioning correctly). These two factors indicate that an interesting case might be made, given the right circumstances.

Of course, this does not apply everywhere. To be able to automatically generate test cases, the following points should be observed:

Are my specifications recorded in a format that is suitable for automated test case generation?
Of course, the specifications should be recorded in such a way that they can be interpreted by your test case generator. It is highly unlikely that specifications written in natural language in a Word document can be read and understood by a piece of code to the extent that correct test case specifications can be derived from it (however, if you have ever achieved this, please let me know :). On the other hand, when (part of) the specifications for your SUT are captured in a formal model, certain types of test cases might be derived from this by an intelligent piece of software. This is sometimes achieved in Model Based Testing approaches.

Also, in order to validate whether business rules are implemented correctly in your SUT, it might be feasible to automatically derive test cases from these rules, given that they are specified in some sort of (semi-)formal language.

I’m sure there are more examples where generating test cases with a single keystroke or mouse click is feasible.

Is there a profit to be gained from the ability to generate test cases automatically?
Of course, the fact that something can be automated doesn’t mean it necessarily should be automated. However, when there are a lot of test cases to be generated, or when specs change frequently throughout the software development process, which occurs more and more often with the rise in popularity of Agile and Scrum methodologies, developing and testing a test case generator might be beneficial. As with the previous factor, I’m sure there are more possibilities for profit here, but these two stand out for me at the moment.

A case study
In a recent project I have been able to successfully implement not only the automated execution of test cases, but also the generation of these test cases directly from the specifications as provided by our client.

The project concerned the testing of a web service that validates fixed-length messages for syntactical correctness, semantical integrity and adherence to a number of business rules. There were around 20 types of messages, each consisting of a couple of hundreds of fields. Each field and each business rule has a corresponding error code that is returned by the server in case either the field specifications or the business rules are violated. Needless to say, that’s a lot of test cases.

Specifying these test cases by hand would take a very long time, would be tiresome as the test cases are highly similar and would therefore be pretty error-prone as well. Even testers get bored every now and then.. However, the similarity and the number of the set of test cases also makes a pretty good case for automating test case generation.

First, we need to determine what types of test cases we can identify and which of these can be generated automatically. In this article, I will focus on the negative test cases, i.e., the test cases for which the web service should return one or more error codes. For this project, I identified the following types of negative test cases:

  • Leave mandatory fields empty
  • Assign alphanumeric values to numeric fields
  • For fields that may only contain values from a predefined enumeration: enter values that are not in the enumeration
  • Simple business rules such as ‘IF field A contains value X THEN field B should contain value Y’
  • More complex business rules such as ‘The message may contain up to three address records whenever the client is of type Z’

I chose to skip the test case where the mandatory field was omitted altogether. In fixed length messages, this will cause all subsequent fields to be out of place, effectively rendering the message useless.

Next, I wrote some lines of code (in Jython, in my case) to read the message specifications (these were provided in Excel format, not ideal but manageable using the Apache POI library) and derive test cases from them. For example, a field with the following characteristics:

  • Mandatory
  • Length 1
  • Numerical
  • Values allowed: 1,2,9

yields the following negative test cases:

  • Leave the field empty
  • Enter value ‘A’ in the field
  • Enter value 3 in the field

Writing the code to generate these test cases took me a day, far shorter than it would have taken to generate all test cases by hand. Let alone what would happen when a new version of the message specs would have arrived somewhere halfway through the testing process..

Next, I had to generate the test messages for each and every test case. I did this by using a test message template, which was effectively a valid message (i.e., it does not generate error messages upon validation), containing all possible fields. Then, for every negative test case, I replaced the correct value for the field under test in that test case with an incorrect value depending on the type of test case. For example, when the test message template looks like this:


and the field under test is the last position in the test message, the generated test messages for the test cases mentioned above look like this:


Then, I’d send the test message to the validation web service and checked whether the response from the web service contained a message stating that the field under test had an error in it, and whether the correct error code was returned by the service.

As a result, I was able to quickly generate literally thousands of test cases, many of which had never been executed before (as there was no time and no-one had though of generating test cases instead of manually specifying them). This resulted in very high test coverage and quick turnaround time, and a very happy customer overall.

Hopefully the case study above shows an example of the power of generating test cases. Again, it might not be achievable or economical everywhere, but when it does, the results may be very beneficial. Whenever system specifications are available in a format that can be processed automatically (such as Excel, text or XML), there might just be an opportunity to save lots of time using test case generation.

Running Selenium Webdriver tests in Jenkins using Ant

In a previous post I introduced a very simple and straightforward way to run data-driven tests in Selenium Webdriver using test data stored in an Excel sheet. In this post, I want to show how to run these tests using a continuous integration (CI-) solution.

My preferred CI-tool is Jenkins, as it is open source, very flexible and easy to use.
First, make sure that Jenkins is set up properly and is running as a service. Installation is very easy, so I won’t go into details here.

I also recommend using Ant as a software build tool to further ease the process of compiling and running our tests. While it is not strictly necessary to use Ant, it will make life a lot easier for us. Again, install Ant and make sure it is running smoothly by typing ant on the command prompt. If it starts asking for a build.xml file, it’s running properly.


Next, open the Selenium Webdriver project in your IDE. Again, I prefer using Eclipse, so the images shown here will be based on Eclipse. Other IDEs such as IntelliJ usually provide the same functionality, it’s just hidden behind different menu options.

Before we start configuring our project for using Ant and running in Jenkins, we are going to add some flexibility to it. Jenkins uses its own workspace and might be running on another server altogether. However, our Selenium project contains a reference to a locally stored Excel data source. Therefore, we are going to add the possibility to provide the path to the data source to be used as an argument to our main method in the Selenium test. In this way, we can simply specify the location of the data source when we run the test. Not only is this necessary to have our test run smoothly in Jenkins, it also adds the possibility to execute several test runs with separate test data sets.

public static void main (String args[]) {
		String strPath;
		if (args.length == 1) {
			strPath = args[0];
		} else {
			strPath = "Z:\\Documents\\Bas\\blog\\datasources\\testdata.xls";
		try {
			// Open the Excel file
			FileInputStream fis = new FileInputStream(new File(strPath).getAbsolutePath());

If an argument is specified when running the main method of our test, we assume this is a relative path to our Excel data source. In order to be able to use it, all we have to do is to get the absolute path for it and off we go. If no argument is specified, we use the default Excel file.

Next, we create a build.xml file that provides Ant with the necessary instructions and details on how to build and run our test. In Eclipse, this can be done easily by right-clicking our project and selecting ‘Export > General > Ant Buildfiles’. After selecting the appropriate project, a build.xml file is generated and added to the root of our project. The example below is a part of the resulting file:

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!-- WARNING: Eclipse auto-generated file.
              Any modifications will be overwritten.
              To include a user specific buildfile here, simply create one in the same
              directory with the processing instruction <?eclipse.ant.import?>
              as the first entry and export the buildfile again. --><project basedir="." default="build" name="seleniumTest">
<property environment="env"/>
<property name="ECLIPSE_HOME" value="C:/Tools/eclipse"/>
<property name="debuglevel" value="source,lines,vars"/>
<property name="target" value="1.7"/>
<property name="source" value="1.7"/>
<path id="seleniumTest.classpath">
    <pathelement location="bin"/>
    <pathelement location="../../../../../vmware-host/Shared Folders/Documents/Bas/blog/libs/selenium-server-standalone-2.37.0.jar"/>
    <pathelement location="../../../../../vmware-host/Shared Folders/Documents/Bas/blog/libs/poi-3.9-20121203.jar"/>
<target name="init">
    <mkdir dir="bin"/>
    <copy includeemptydirs="false" todir="bin">
        <fileset dir="src">
            <exclude name="**/*.java"/>
<target name="clean">
    <delete dir="bin"/>

Before we can run our tests using Ant, we need to make two modifications.

First, we need to clean up the classpath as we want to use clear and relative paths. Make sure that the necessary libraries can be found on the designated locations. These are specified relative to the location of the build.xml file.

<path id="seleniumTest.classpath">
    <pathelement location="bin"/>
    <pathelement location="libs/selenium-server-standalone-2.37.0.jar"/>
    <pathelement location="libs/poi-3.9-20121203.jar"/>

Next, we need to make sure that our Excel data source is specified as an argument in the designated Ant target:

<target name="ExcelDataDriven">
    <java classname="com.ontestautomation.selenium.ExcelDataDriven" failonerror="true" fork="yes">
        <arg line="datasources/testdata.xls"/>
        <classpath refid="seleniumTest.classpath"/>

Now, we can execute our test using Ant either in Eclipse or at the command line. When you choose the latter, go to the subdirectory for the Selenium project in your workspace (build.xml should be located there) and execute ant <> (ant ExcelDataDriven in this case). You’ll see that the test is run successfully using Ant.


The final step is to have this step performed by Jenkins. This should be very straightforward now. Create a new job in Jenkins and add ‘Invoke Ant’ as a build step. Specify the correct target (again, ExcelDataDriven in our case).


Make sure that all referenced libraries and data sources can be found at the correct locations in the workspace for the Jenkins job (this is where using relative paths comes in handy!). Normally, you would do this using some sort of version control sytem such as Subversion. Next, schedule a build for the job, which should run smoothly now:


That’s it, we’ve now successfully run our Selenium Webdriver tests in Jenkins using Ant. One step closer to a successful continuous integration approach!

Best practice: focus on repeatability of your automated tests

This is the first installment in a series of posts on test automation best practices. Notwithstanding the rapid growth and evolution of the test automation field, a number of best practices can be identified that stand the test of time. Adhering to these best practices will improve the added value of your automated tests, no matter the scale or scope of the test, or the technology or tools that are used to design, implement or execute automated tests.

In order for your automated test suites to be truly efficient, they should be set up with repeatability in mind. This means that your tests should execute with the click of a button, or by entering a command in the command prompt, again and again, without the need for manual intervention during or in between test runs. They should also yield the same (or comparable) test results every single time. Except when the system under test changes or fails, of course.

To achieve or improve repeatability, you need to pay attention to a number of things during the implementation of your automated tests. I will address some of these in this article. There are probably lots of other aspects to be considered, but these stand out for me.

One disclaimer: the repeatability factor does not apply (or applies to a far lesser extent) to projects where there’s just a single test run to be executed, for instance after a conversion or a migration project. If you’re involved in such a project, it’s probably not worth it to put extra effort in achieving repeatability of your automated tests.

Start small
As with every software development project, it is best to start small when implementing automated tests. Automate one or two test cases, or even just one or two steps of the process to be automated, and execute them over and over again to make sure they are stable and repeatable. Once your small test cases are proven to be repeatable you can build on them to create larger test suites. Make sure you prove that every major change you make to your tests does not compromise the repeatability of your tests.

Watch your test data
An important issue when designing and implementing repeatable automated tests is the use of test data. Scripts that alter or consume test data need some extra attention with regards to repeatability. A test data object, such as a customer, an order, etc., used in a certain test run may be altered or removed during that run, rendering it unsuitable or unavailable for subsequent test runs.

Roughly speaking, there are three possible approaches for dealing with test data that is altered during a test run:

  • Create the test data during the test run. For example, if your test script covers the processing of an order, have your script create a new order before processing it to make sure there’s always an order to be processed
  • Reset the test data to its original state after the test run. For example, if your test script covers changing a customer’s address to a foreign location, reset it to its original value after the test script has been executed (through whichever interface available).
  • Select the test data to be used at the start of your test run. Rather than using previously defined sets of test data, have your script perform a query on the available test data set to select a test data object to use in a particular test run. Make sure that your script can handle occasions where there’s no suitable test data object available.

Be ready for continuous integration
With the current trend of test and development teams working closer together in increasingly shorter development and test cycles (think Agile / Scrum and DevOps), continuous integration (CI) is applied not only for development tasks, but for system and integration testing as well. In order to be able to keep up with the development team, automated tests should seamlessly integrate with the continuous integration platform in use. Most open source and COTS automated test tools provide a command line interface to execute test runs and export and distribute test result reports. This doesn’t make your test scripts automagically suited for use in a CI environment. Only test scripts or frameworks that can be run again and again without the need for manual intervention can be successfully integrated in the CI process, so make sure yours fit the bill!

A schematic representation of continuous integration

A schematic representation of continuous integration

Effects of repeatability on the acceptance and the ROI of test automation
Once you have managed to control the repeatability of your automated test scripts, you should see some pretty positive results with regards to the acceptance of automated testing and the ROI associated with the test automation project:

  • Repeatable tests can be run on demand, as often as required, leading to a dramatic reduction of the cost per test run and the time needed to complete a development/test cycle
  • Automated tests that can run unattended and that can be repeated on demand will appeal to everybody from developers to upper management, increasing its perceived value and ultimately also increasing the trust in the product delivered by your team.

Are your tests as repeatable as they can be? Let me know how you achieved your degree of repeatability and the issues you had to overcome!