Manual
 

The video 'Scripting in QF-Test (Basics)' explains the basic concepts about scripting.

If you want to know more about scripting have a look at the video 'Scripting in QF-Test (Advanced) explains the basic concepts about scripting.

One of QF-Test's benefits is that complex tests can be created without writing a single line of code. However, there are limits to what can be achieved with a GUI alone. When testing a program which writes to a database, for example, one might want to verify that the actual values written to the database are correct; or one might want to read values from a database or a file and use these to drive a test. All this and more is possible with the help of powerful scripting languages like Jython, Groovy or JavaScript.

4.2+ While Jython is supported since the beginning of QF-Test, Groovy has found its way into QF-Test a bit later (QF-Test version 3). This language might be more convenient than Jython for those who are familiar with Java. Version 4.2 enabled JavaScript which might be more suitable for web developers. It's mainly a matter of individual preference whether to utilize Jython, Groovy or JavaScript scripting inside QF-Test.

In this chapter the basics of the scripting features available in all supported languages are explained. Most of the examples can be applied exactly or with few changes in other script languages. Methods calls which vary in syntax are exemplified in the affected languages. Particularities of the script languages are described in the sections Fundamentals of the Jython integration, Scripting with Groovy and Scripting with JavaScript.

3.0+ The scripting language to use for a given 'Server script' or 'SUT script' node is determined by its 'Script language' attribute, so you can mix all three languages within a test-suite. The default language to use for newly created script nodes can be set via the option Default script language for script nodes.

The approach to scripting in QF-Test is inverse from that of other GUI test tools. Instead of driving the whole test from a script, QF-Test embeds scripts into the test-suite. This is achieved with the two nodes 'Server script' and 'SUT script'.

Both nodes have a 'Script' attribute for the actual code.

		Figure 12.1:  Detail view of a 'Server script' with help window for rc methods

3.0+ The internal script editor has some useful features to ease the typing of code. Reserved keywords, built-in functions, standard types, literals and comments are highlighted. Indentation is handled automatically inside of code blocks. With [TAB] and [Shift-TAB] respectively several selected lines can be indented manually.

However, the probably most useful feature - at least for the QF-Test newbie - might be the input assistance for many built-in methods. Type, for example, rc. and maybe some initial letters of a method name. Then press [Ctrl-Space] to open a pop-up window displaying the appropriate methods and descriptions of QF-Test's run-context (cf. chapter 44). Select one of the methods and confirm with [Return] to insert it into the script code. To get a list of all objects equipped with help, just press [Ctrl-Space] with the mouse cursor positioned after white space.

'Server scripts' are useful for tasks like calculating the values of variables or reading and parsing data from a file and using it to drive a test. 'SUT scripts' on the other hand give full access to the components of the SUT and to every Java API that the SUT exposes. An 'SUT script' might be used to retrieve or check values in the SUT to which QF-Test doesn't have access. The 'SUT script' node has a 'Client' attribute which requires the name of the SUT client to run in.

'Server scripts' are run in script interpreters for the different script languages embedded in QF-Test itself, while 'SUT scripts' are run in a script interpreter embedded in the SUT. These interpreters are independent of each other and do not share any state. However, QF-Test uses the RMI connection between itself and the SUT for seamless integration of 'SUT scripts' into the execution of a test.

Through the menu items »Extras«-»Jython terminal...« or »Extras«-»Groovy terminal...« etc. you can open a window with an interactive command prompt for the language interpreter embedded in QF-Test. You can use this terminal to experiment with Jython scripts, get a feeling for the language, but also to try out some sophisticated stuff like setting up database connections. The keystrokes [Ctrl-Up] and [Ctrl-Down] let you cycle through previous input and you can also edit any other line or mark a region in the terminal and simply press [Return] to send it to the interpreter. In that case QF-Test will filter the '>>>' and '...' prompts from previous interpreter output.

Similar terminals are available for each SUT client. The respective menu items are located below the »Clients« menu.

Note When working in a SUT script terminal, there's one thing you need to be aware of: The commands issued to the interpreter are not executed on the event dispatch thread, contrary to commands executed via 'SUT script' nodes. This may not mean anything to you and most of the time it doesn't cause any problems, but it may deadlock your application if you access any Swing or SWT components or invoke their methods. To avoid that, QF-Test provides the global method runAWT (and runSWT respectively) that executes arbitrary code on the event dispatch thread. For example, to get the number of visible nodes in a JTree component named tree, use runAWT("tree.getRowCount()") (or runAWT { tree.getRowCount() } in Groovy) to be on the safe side.

When executing 'Server scripts' and 'SUT scripts', QF-Test provides a special environment in which a variable named rc is bound. This variable represents the run-context which encapsulates the current state of the execution of the test. It provides an interface (fully documented in section 44.6) for accessing QF-Test variables, for calling QF-Test procedures and can be used to add messages to the run-log. To 'SUT scripts' it also provides access to the actual Java components of the SUT's GUI.

For those cases where no run-context is available, i.e. Resolvers, TestRunListeners, code executing in a background thread etc. QF-Test also provides a module called qf with useful generic methods for logging and other things. Please see section 44.7 for details.

One thing the run-context can be used for is to add arbitrary messages to the run-log that QF-Test generates for each test-run. These messages may also be flagged as warnings or errors.

rc.logMessage("This is a plain message")
rc.logWarning("This is a warning")
rc.logError("This is an error")

When working with compact run-logs (which is strongly encouraged, see the option Create compact run-log), nodes which most likely will not be needed for error analysis may be deleted from the run-log to preserve memory. This does not apply to error messages (rc.logError). They are kept, along with about 100 nodes preceding the error. Warnings (rc.logWarning) are also kept, however, without preceding nodes. Normal messages (rc.logMessage) may be subject to deletion. If you really need to make sure that a message will definitely be kept in the run-log you can enforce this by specifying the optional second parameter dontcompactify, e.g.

rc.logMessage("This message will not be removed", dontcompactify=true)
# or simply
rc.logMessage("This message will not be removed", 1)

Most of the time logging messages is tied to evaluating some condition. In that case, it is often desirable to get a result in the HTML or XML report equivalent to that of a 'Check' node. The methods rc.check and rc.checkEqual will do just that:

var = 0
rc.check(var == 0, "Value of var is 0")
rc.checkEqual('${system:user.language}', 'en', "English locale required",
              rc.EXCEPTION)

The optional last argument changes the error level in case of failure. Possible values are rc.EXCEPTION, rc.ERROR, rc.OK or rc.WARNING.

QF-Test has different kinds of variables. On the one hand you find variables belonging to the QF-Test environment and on the other variables of the script languages. Variables of the script languages are separated in server and SUT side variables of the specific script interpreter. The following graphic clarifies theses differences:

		Figure 12.2:  Overview of the types of variables in QF-Test

To share the different kinds of variables between QF-Test and the script interpreters provides the rc object which has several methods for the purpose. The methods are explained in the next section.

Using QF-Test variables in scripts is not difficult. You can use the run-context's lookup method (see section 44.6 for API reference) whenever you want to access a QF-Test value as a string.

# access a simple variable
text = rc.lookup("someText")
# access a property or resource
version = rc.lookup("qftest", "version")

To make the results of a script available during further test execution, values can be stored in global or local variables. The effect is identical to that of a 'Set variable' node. The corresponding methods in the run-context are rc.setGlobal and rc.setLocal.

# Test if the file /tmp/somefile exists
from java.io import File
rc.setGlobal("fileExists", File("/tmp/somefile").exists())

After executing the above example $(fileExists) will expand to true if the file /tmp/somefile exists and to false if it doesn't.

To clear a variable, set it to None, to clear all global variables use rc.clearGlobals() from a 'Server script'.

Sometimes it is helpful to have a variable available in several scripting nodes of the same language. If the value of the variable is not a simple string or integer, it is normally not sufficient to use rc.setGlobal(...) to store it in a global QF-Test variable because the value will be converted to a string in the process. Instead, such a variable should be declared global as shown in the following example.

global globalVar
globalVar = 10000

The globalVar is now accessible within all further scripting nodes of the same type ('Server scripts' or 'SUT scripts' of the same client). For changing the value of globalVar within another script, the global declaration is necessary again. Otherwise, a new local variable is created instead of accessing the existing global. Use the del statement to remove a global Jython variable:

global globalVar
del globalVar

In Groovy and JavaScript the global variables declaration is even easier than in Jython. All variables that are not declared locally are assumed to be global.

myGlobal = 'global'

assert myGlobal == 'global'
def globals = binding.variables
assert globals['myGlobal'] == 'global'
globals.remove('myGlobal')
assert globals.find { it == 'myGlobal' } == null

Sometimes one would like to use variable values that have been defined in one interpreter in a different interpreter. For example, an 'SUT script' might have been used to create a list of items displayed in a table. Later we want to iterate over that list in a 'Server script'.

To simplify such tasks, the run-context provides a symmetrical set of methods to access or set global variables in a different interpreter. For 'SUT scripts' these methods are named toServer and fromServer. The corresponding 'Server script' methods are toSUT and fromSUT.

The following example illustrates how an 'SUT script' can set a global variable in the QF-Test Jython interpreter:

cellValues = []
table = rc.lookup("idOfTable")
for i in range(table.getRowCount()):
    cellValues.append(table.getValueAt(i, 0))
rc.toServer(tableCells=cellValues)

After the above script is run, the global variable named "tableCells" in the QF-Test Jython interpreter will hold the array of cell values.

Note The cell values in the above example are not necessarily strings. They could be numbers, date values, anything. Unfortunately Jython's pickle mechanism isn't smart enough to transport instances of Java classes (not even realizable ones), so the whole exchange mechanism is limited to primitive types like strings and numbers, along with Jython objects and structures like arrays and dictionaries.

For 'SUT scripts' the run-context provides an additional method that is extremely useful. Calling rc.getComponent("componentId") will retrieve the information of the 'Component' node in the test-suite with the 'QF-Test ID' "componentId" and pass that to QF-Test's component recognition mechanism. The whole process is basically the same as when simulating an event, including the possible exceptions if the component cannot be found.

If the component is located, it will be passed to Jython, not as some abstract data but as the actual Java object. All methods exposed by the Java API for the component's class can now be invoked to retrieve information or achieve effects which are not possible through the GUI alone. To get a list of a component's method see section 5.5.

# get the custom password field
field = rc.getComponent("tfPassword")
# read its encrypted value
passwd = field.getCryptedText()
rc.setGlobal("passwd", passwd)
# get the table component
table = rc.getComponent("tabAddresses")
# get the number of rows
rows = table.getRowCount()
rc.setGlobal("tableRows", rows)

You can also access sub-items this way. If the componentId parameter references an item, the result of the getComponent call is a pair, the component and the item's index. The index can be used to retrieve the actual value. The following example shows how to get the value of a table cell. Note the convenient way Jython supports sequence unpacking during assignment.

# first get the table and index
table, (row,column) = rc.getComponent("tableAddresses@Name@Greg")
# then get the value of the table cell
cell = table.getValueAt(row, column)

The run-context can also be used to call back into QF-Test and execute a 'Procedure' node.

rc.callProcedure("text.clearField",
         {"component": "nameField", "message" : "nameField cleared"})

In the example above the 'Procedure' named "clearField" in the 'Package' named "text" will be called. The parameter named "component" is set to the value "nameField" and the parameter named "message" is set to the value "nameField cleared".

The same example with Groovy syntax:

rc.callProcedure("text.clearField",
         ["component" : "nameField", "message" : "nameField cleared"])

And in JavaScript:

rc.callProcedure("text.clearField",
         {"component" : "nameField", "message" : "nameField cleared"})

The value returned by the 'Procedure' through a 'Return' node is returned as the result of the rc.callProcedure call.

Note Great care must be taken when using rc.callProcedure(...) in 'SUT script' nodes. Only short-running 'Procedures' should be called that won't trigger overly complex actions in the SUT. Otherwise, a DeadlockTimeoutException might be caused. For data-driven tests where for some reason the data must be determined in the SUT, use rc.toServer(...) to transfer the values to QF-Test interpreter, then drive the test from a 'Server script' node where these restrictions do not apply.

Many of the options described in chapter 36 can also be set at runtime via rc.setOption. Constants for option names are predefined in the class Options. It is automatically available for all script languages.

A real-life example where this might be useful is if you want to replay an event on a disabled component, so you need to temporarily disable QF-Test's check for the enabled/disabled state:

rc.setOption(Options.OPT_PLAY_THROW_DISABLED_EXCEPTION, false)

After replaying this special event, the original value read from the configuration file or set in the option dialog can be restored by unsetting the option as the following example shows:

rc.unsetOption(Options.OPT_PLAY_THROW_DISABLED_EXCEPTION)

NoteBe sure to set QF-Test options in a 'Server script' node and SUT options in an 'SUT script' node, otherwise the setting will have no effect. The option documentation in chapter 36 shows which one to use.

You might face a situation where you want to work with a component which you have to search before working with it. Sometimes recording all required components can be exhaustive or might be too complicated. For such cases you can use the method rc.overrideElement to set the found component (either by generic components or via scripting) to a QF-Test component. Now you can work with the assigned component and use all available QF-Test nodes.

Let's imagine that we have a panel and we want to work with the first textfield, but because of changing textfields we cannot rely on the standard way of the recognition. Now we can implement a script, which looks for the first textfield and assigns that textfield to the PriorityAwtSwingComponent from the standard library qfs.qft. Once we have executed that script we can work with any QF-Test nodes using the PriorityAwtSwingComponent, which actually performs all actions on the found textfield.

panel = rc.getComponent("myPanel")
for component in panel.getComponents():
  if qf.isInstance(component, "javax.swing.JTextField"):
     rc.overrideElement("PriorityAwtSwingComponent", component)
     break
          

This concept is very useful if you know an algorithm to determine the target component of your test-steps.

You can find such priority-components for all engines in the standard library qfs.qft. You can also find an illustrative example in the provided demo test-suite carconfig_en.qft, located in the directory demo/carconfig in your QF-Test installation.

Python is an excellent, object oriented scripting language written in C by Guido van Rossum. A wealth of information including an excellent Python tutorial is available at http://www.python.org. Python is a standard language that has been around for years with extensive freely accessible documentation. Therefore, this manual only explains how Jython is integrated into QF-Test, not the language itself. Python is a very natural language. Its greatest strength is the readability of Python scripts, so you should have no problems following the examples.

Jython (formerly called JPython) is a Java implementation of the language Python. It has the same syntax as Python and almost the same set of features. The object systems of Java and Jython are very similar and Jython can be integrated seamlessly into applications like QF-Test. This makes it an invaluable tool for Java scripting. Jython has its own web page at http://www.jython.org. There is also an extensive tutorial available which may help you get started with this scripting language.

QF-Test uses Jython version 2.7 which supports a large majority of the standard Python library.

NoteIn Jython QF-Test variables with the syntax $(var) or ${group:name} are expanded before the execution of the script. This can lead to unexpected behavior. rc.lookup(...), which will be evaluated during execution of the script, is the preferred method in this case (see subsection 12.2.3.1 for details).

Modules for Jython in QF-Test are just like standard Python modules. You can import the modules into QF-Test scripts and call their methods, which simplifies the development of complex scripts and increases maintainability since modules are available across test-suites.

Modules intended to be shared between test-suites should be placed in the directory jython under QF-Test's root directory. Modules written specifically for one test-suite can also be placed in the test-suite's directory. The version-specific directory qftest-5.1.0/jython/Lib is reserved for modules provided by Quality First Software GmbH. Jython modules must have the file extension .py.

The following Jython module defines a procedure sorting an array of numbers.

def insertionSort(alist):
    for index in range(1,len(alist)):

        currentvalue = alist[index]
        position = index

        while position>0 and alist[position-1]>currentvalue:
            alist[position]=alist[position-1]
            position = position-1

        alist[position]=currentvalue

The procedure defined in above module is beeing called in the following Jython script:

import pysort

alist = [54,26,93,17,77,31,44,55,20]
pysort.insertionSort(alist)
print(alist)

Python comes with a simple line-oriented debugger called pdb. Among its useful features is the ability for post-mortem debugging, i.e. analyzing why a script failed with an exception. In Python you can simply import the pdb package and run pdb.pm() after an exception. This will put you in a debugger environment where you can examine the variable bindings in effect at the time of failure and also navigate up to the call stack to examine the variables there. It is somewhat similar to analyzing a core dump of a C application.

Though Jython comes with pdb, the debugger doesn't work very well inside QF-Test for various reasons. But at least post-mortem debugging of Jython scripts is supported from the Jython terminals (see section 12.3). After a 'Server script' node fails, open QF-Test's Jython terminal, for a failed 'SUT script' node open the respective SUT Jython terminal, then just execute debug(). This should have a similar effect as pdb.pm() described above. For further information about the Python debugger please see the documentation for pdb at https://docs.python.org/2/library/pdb.html.

Jython now has a real boolean type with values True and False whereas in older versions integer values 0 and 1 served as boolean values. This can cause problems if boolean results from calls like file.exists() are assigned to a QF-Test variable, e.g. "fileExists" and later checked in a 'Condition' attribute in the form $(fileExists) == 1. Such conditions generally be written as just $(fileExists) which works well with all Jython versions.

All Java strings are sequences of 16-bit characters. Python's original strings are made of 8-bit characters. Later, unicode strings with 16-bit characters were added. Jython literal strings like "abc" are 8-bit, prepending 'u' for u"abc" turns them into unicode strings.

In Jython 2.2, Java strings were converted to 8-bit Python strings based on the default encoding of the Java VM, typically ISO-8859-1 (also known as latin-1) in western countries. In Jython 2.5, every Java string is now interpreted as a unicode Jython string. This results in a lot more implicit conversion between 8-bit and unicode strings, for example when concatenating a Java string - now converted to unicode - and a literal string like rc.lookup("path") + "/file". Most of the time this works well, but if the literal string contains characters outside the 7-bit ASCII character-set, things start to get messy. The default encoding for 8-bit Jython characters can be specified in the option Default character encoding for Jython with a default of latin-1 for maximum backwards compatibility. On the upside it is now possible to have default encodings other than latin-1 and to specify literal strings of characters in international character sets.

One thing to watch out for is existing code of the form

import types
if type(somevar) == types.StringType:
    ...

The type types.StringType is the 8-bit string. It does not match unicode strings. To test whether some variable is a Jython string, regardless of whether it's 8-bit or unicode, change that to

import types
if type(somevar) in types.StringTypes:
    ...

One new requirement - coming from newer Python versions - is that Python module files containing characters outside the 7-bit ASCII character must specify the character encoding to be used in a comment line close to the top of the file, e.g.

# coding: latin-1

Please see http://www.python.org/peps/pep-0263.html for details.

This simple operation is surprisingly difficult in Jython. Given a Java object you would expect to simply write obj.getClass().getName(). For some objects this works fine, for others it fails with a cryptic message. This can be very frustrating. Things go wrong whenever there is another getName method defined by the class, which is the case for AWT Component, so getting the class name this way fails for all AWT/Swing component classes.

In Jython 2.2.1 the accepted workaround was to use the Python idiom obj.__class__.__name__. This no longer works in Jython 2.5 because it no longer returns the fully qualified class name, only the last part. Instead of java.lang.String you now get just String. The only solution that reliably works for version 2.5 is:

from java.lang import Class
Class.getName(obj.getClass())

This also works for 2.2, but it is not nice, so we initiated a new convenience module with utility methods called qf that gets imported automatically. As a result you can now simply write

qf.getClassName(obj).

We are going to close this section with a complex example, combining features from Jython and QF-Test to execute a data-driven test. For the example we assume that a simple table with the three columns "Name", "Age" and "Address" should be filled with values read from a file. The file is assumed to be in "comma-separated-values" format with "|" as the separator character, one line per table-row, e.g.:

John Smith|45|Some street, some town
Julia Black|35|Another street, same town

The example verifies the SUT's functionality in creating new table rows. It calls a QF-Test procedure that takes the three parameters, "name", "age", and "address", creates a new table-row and fills it with these values. Then the Jython script is used to read and parse the data from the file, iterate over the data-sets and call back to QF-Test for each table-row to be created. The name of the file to read is passed in a QF-Test variable named "filename". After filling the table, the script compares the state of the actual table component with the data read from the file to make sure everything is OK.

import string
data = []
# read the data from the file
fd = open(rc.lookup("filename"), "r")
line = fd.readline()
while line:
    # remove whitespace
    line = string.strip(line)
    # split the line into separate fields
    # and add them to the data array
    if len(line) > 0:
        data.append(string.split(line, "|"))
    line = fd.readline()

# now iterate over the rows
for row in data:
    # call a qftest procedure to create
    # one new table row
    rc.callProcedure("table.createRow",
                     {"name": row[0], "age": row[1],
                      "address": row[2]})

# verify that the table-rows have been filled correctly
table = rc.getComponent("tabAddresses")

# check the number of rows
rc.check(table.getRowCount() == len(data), "Row count")
if table.getRowCount() == len(data):
    # check each row
    for i in range(len(data)):
        rc.check(table.getValueAt(i, 0)) == data[i][0],
                 "Name in row " + str(i))
        rc.check(table.getValueAt(i, 1)) == data[i][1],
                 "Age in row " + str(i))
        rc.check(table.getValueAt(i, 2)) == data[i][2],
                 "Address in row " + str(i))

Of course, the example above serves only as an illustration. It is too complex to be edited comfortably in QF-Test and too much is hard-coded, so it is not easily reusable. For real use, the code to read and parse the file should be parameterized and moved to a module, as should the code that verifies the table.

This is done in the following Jython script with the methods loadTable to read the data from the file and verifyTable to verify the results. It is saved in a module named csvtable.py. An example module is provided in qftest-5.1.0/doc/tutorial/csvtable.py. Following is a simplified version:

import string

def loadTable(file, separator="|"):
    data = []
    fd = open(file, "r")
    line = fd.readline()
    while line:
        line = string.strip(line)
        if len(line) > 0:
            data.append(string.split(line,separator))
        line = fd.readline()
    return data

def verifyTable(rc, table, data):
    ret = 1
    # check the number of rows
    if table.getRowCount() != len(data):
        if rc:
            rc.logError("Row count mismatch")
        return 0
    # check each row
    for i in range(len(data)):
        row = data[i]
        # check the number of columns
        if table.getModel().getColumnCount() != len(row):
            if rc:
                rc.logError("Column count mismatch " +
                            "in row " + str(i))
            ret = 0
        else:
            # check each cell
            for j in range(len(row)):
                val = table.getModel().getValueAt(i, j)
                if str(val) != row[j]:
                    if rc:
                        rc.logError("Mismatch in row " +
                                    str(i) + " column " +
                                    str(j))
                    ret = 0
    return ret

The code above should look familiar. It is an improved version of parts of example 12.21. With that module in place, the code that has to be written in QF-Test is reduced to:

import csvtable
# load the data
data = csvtable.loadTable(rc.lookup("filename"))
# now iterate over the rows
for row in data:
    # call a qftest procedure to create
    # one new table row
    rc.callProcedure("table.createRow",
                     {"name": row[0], "age": row[1],
                      "address": row[2]})

# verify that the table-rows have been filled correctly
table = rc.getComponent("tabAddresses")
csvtable.verifyTable(rc, table, data)

For more complex import of data QF-Test can be extended with existing Python modules. For example, at http://python-dsv.sourceforge.net/ an excellent module for very flexible CSV import is freely available.

Groovy is another established scripting language for the Java Platform. It was invented by James Strachan and Bob McWhirter in 2003. All you need for doing Groovy is a Java Runtime Environment (JRE) and the groovy-all.jar file. This library contains a compiler to create Java class files and provides the runtime when using that classes in the Java Virtual Machine (JVM). You may think of Groovy as being Java with an additional .jar file. In contrast to Java, Groovy is a dynamic language, meaning that the behavior of an object is determined at runtime. Groovy also allows to load classes from sources without creating class files. Finally, it is easy to embed Groovy scripts into Java applications like QF-Test.

The Groovy syntax is similar to Java, maybe more expressive and easier to read. When coming from Java you can embrace the Groovy style step by step. Of course we cannot explain all aspects of the Groovy language here. For in-depth information, please take a look at the Groovy home page at http://groovy-lang.org/ or read the excellent book "Groovy in Action" by Dierk Koenig and others. Perhaps the following tips may help a Java programmer getting started with Groovy.

• The semicolon is optional as long as a line contains only one statement.
• Parentheses are sometimes optional, e. g. println 'hello qfs' means the same as println('hello qfs').
• Use for (i in 0..<len) { ... } instead of for (int i = 0; i < len; i++) { ... }.
• The following imports are made by default: java.lang.*, java.util.*, java.io.*, java.net.*, groovy.lang.*, groovy.util.*, java.math.BigInteger, java.math.BigDecimal.
• Everything is an object, even integers like '1' or booleans like 'true'.
• Instead of using getter and setter methods like obj.getXxx(), you can simply write obj.xxx to access a property.
• The operator == checks for equality, not identity, so you can write if (somevar == "somestring") instead of if (somevar.equals("somestring")). The method is() checks for identity.
• Variables have a dynamic type when being defined with the def keyword. Using def x = 1 allows for example to assign a String value to the variable x later in the script.
• Arrays are defined differently from Java, e. g. int[] a = [1, 2, 3] or def a = [1, 2, 3] as int[]. With def a = [1, 2, 3] you define a List in Groovy.
• Groovy extends the Java library by defining a set of extra methods for many classes. Thus, you can for example apply an isInteger() method to any String object in a Groovy script. That's what is called GDK (according to the JDK in Java). To get a list of those methods for an arbitrary object obj, you can simply invoke obj.class.metaClass.metaMethods.name or use the following example:

import groovy.inspect.Inspector

def s = 'abc'
def inspector = new Inspector(s)
def mm = inspector.getMetaMethods().toList().sort() {
    it[Inspector.MEMBER_NAME_IDX] }
for (m in mm) {
    println(m[Inspector.MEMBER_TYPE_IDX] + ' ' +
            m[Inspector.MEMBER_NAME_IDX] +
            '(' + m[Inspector.MEMBER_PARAMS_IDX] + ')')
}

• Inner classes are not supported, in most cases you can use Closures instead. A Closure is an object which represents a piece of code. It can take parameters and return a value. Like a block, a Closure is defined with curly braces { ... }. Blocks only exist in context with a class, an interface, static or object initializers, method bodies, if, else, synchronized, for, while, switch, try, catch, and finally. Every other occurrence of {...} is a Closure. As an example let's take a look at the eachFileMatch GDK method of the File class. It takes two parameters, a filter (e. g. a Pattern) and a Closure. That Closure takes itself a parameter, a File object for the current file.

def dir = rc.lookup('qftest', 'suite.dir')
def pattern = ~/.*\.qft/
def files = []
new File(dir).eachFileMatch(pattern) { file ->
    files.add(file.name)
}
files.each {
    // A single Closure argument can also be referred with "it"
    rc.logMessage(it)
}

• Working with Lists and Maps is simpler than in Java.

def myList = [1, 2, 3]
assert myList.size() == 3
assert myList[0] == 1
myList.add(4)

def myMap = [a:1, b:2, c:3]
assert myMap['a'] == 1
myMap.each {
    this.println it.value
}

Just like Java classes, Groovy source files (.groovy) can be organized in packages. Those intended to be shared between test-suites should be placed in the directory groovy under QF-Test's root directory. Others that are written specifically for one test-suite can also be placed in the directory of the test-suite. The version-specific directory qftest-5.1.0/groovy is reserved for Groovy files provided by Quality First Software GmbH.

package my

class MyModule
{
    public static int add(int a, int b)
    {
        return a + b
    }
}

The file MyModule.groovy could be saved in a sub directory my below the suite directory. Then you can use the add method from MyModule as follows:

import my.MyModule as MyLib

assert MyLib.add(2, 3) == 5

This code also shows another groovy feature: Type aliasing. By using import and as in combination you can reference a class by a name of your choice.

JavaScript has become the most widely used programming language in the web area and is one of the most popular script languages. QF-Test supports scripting with ECMAScript, which provides a common standard for the variety of different implementations of JavaScript.

QF-Test must run with at least Java 8 to use JavaScript.

It is possible to write code for the ECMAScript 6 standard. QF-Test automatically transpiles the code to the EcmaScript 5 standard before the execution.

Special features of JavaScript as compared to other programming languages:

• There are two different null values: undefined and null. A variable is undefined when it has no value. null is an intended null value that has to be assigned.
• The == operator checks for equality instead of identity. So you can use if (somevar == "somestring") to check for equality. To check for identity use the === operator.
• Variables declared with the let keyword are dynamically typed. E.g. let x = 1 makes it possible to assign String to x. Constants can be declared with const.

The following example shows how functionality can be transfered in a module. The module must be placed in the javascript directory inside the QF-Test root directory. The module can look like this:

var fibonacci = function(n) {
   return n < 1 ? 0
        : n <= 2 ? 1
        : fibonacci(n - 1) + fibonacci(n - 2);
}

function sumDigits(number) {
  var str = number.toString();
  var sum = 0;

  for (var i = 0; i < str.length; i++) {
    sum += parseInt(str.charAt(i), 10);
  }

  return sum;
}
// Module exports (Node.js style)
exports.fibonacci = fibonacci;
exports.sumDigits = sumDigits;

The moremath.js module defines the two function: fibonacci and sumDigits.

Each function has to be exported to . This can be achieved via Node.js like function exports.

The following code can now be used inside the script node to take advantage of the moremath.js modules functions:

moremath = require('moremath');

console.log(moremath.fibonacci(13));
console.log(moremath.sumDigits(123));

There are multiple ways to import modules. Modules provided by QF-Test can be imported using the import function.

import {Autowin} from 'autowin';
Autowin.doClickHard(0, 0, true);

Java classes can also be imported using the import function.

import {File} from 'java.io';

It is also possible to use the "require" function for importing npm modules, which are explained in the following section.

npm is a package manager for JavaScript with over 350.000 packages. The available packages are listed here https://www.npmjs.com/. The packages can be used in QF-Test scripts. They need to be installed in the javascript folder of the QF-Test root directory.

npm install underscore

This line installs the npm underscore package from the os command line.

There are a few npm modules that are incompatible with the ECMAScript standard as they were written for Node.js.

_ = require('underscore');
func = function(num){ return num % 2 == 0; }
let evens = _.filter([1, 2, 3, 4, 5, 6], func);
console.log(evens);

Besides console.log() there is another method implemented in QF-Test to show output on the terminal. Note that this print is not defined in ECMAScript and was added for convenience in QF-Test.

print([1,2,3,4]);

JavaScript scripts are not executed inside the browser but in a specific engine on the server or SUT side. This engine is called Oracle Nashorn Engine and comes with JDK 8. It allows the execution of EcmaScript directly in the JVM.

Last update: 7/8/2020 Copyright © 1999-2020 Quality First Software GmbH