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TDDD04 Software Testing

Lab 2: Symbolic execution and test-case generation


Purpose

This short lab assignment will help you develop an understanding of contemporary tools and techniques that can be used to assess program behavior and generate test cases. You will use a research tool called JPF, which is used in Software Engineering research on the analysis of program behavior.

Introduction

Java Pathfinder is developed as a joint research project, to create a platform for symbolic execution, test-case generation and verification of software. It has been used in a number of research projects and is available as open source software that can be used for many different kinds of software analysis. In this lab assignment, you will work with the specific JPF projects jpf-core and jpf-symbc. You will follow a series of tutorial assignments pertaining to the use of JPF, and the symbolic execution engine in jpf-symbc, and answer questions related to the technology underlying them.

Preparations

First, you need to clone the Eclipse project in your Eclipse workspace, and create an Eclipse project with the same name as the project ("jpf-test"). By creating a project with the same name, Eclipse will import the existing project and any settings that we have already made, such as setting the classpath to a suitable value for our SU lab rooms.

Using JPF means that you launch the JPF virtual machine and pass parameters, either using command line switches or property files, to determine the behavior you would like. For each of the scenarios below, we want you to use an Eclipse launch configurations to determine the invocation of JPF. Common to all of them is that you launch the JPF main class (see picture below).

During the execution of your program, JPF can monitor events in your program that would cause the program to throw an uncaught exception, manipulate how bytecode instructions are to be interpreted, and in general use the concept of listeners (see the documentation in the jpf-core project for more information) to verify program behavior.

Before you proceed, please read the instructions on the JPF main project page on

By default, there are some configuration options that you will need to use for all the excercises below, as parameters specified in the launch configuration to JPF. First, you will need to specify the classpath that JPF will use when searching for your classes. Second, you will need to specify the main class of your program, as a point of entry for JPF. It may look something like this, for the main class race.Deadlock:

+classpath=${workspace_loc:jpf-test}/bin
race.Deadlock
Here is an example of how these parameters would be specified in a launch configuration in Eclipse:

Concurrency testing 1: Deadlock detection

The class race.Deadlock contains two classes Updater1 and Updater2 that attempt to modify the same Pair object. However, in doing so they lock the two fields x and y in different order, possibly causing a deadlock during execution. A deadlock prevents either thread from executing as they have both locked resources for one another.

JPF is configured to detect deadlocks by default (see the "Properties" section of the jpf-core documentation).

The configuration options that you will find useful for this excercise are probably those related to the report you get at the end:

 +report.console.property_violation=error,trace 
This option indicates that you will get a stack trace of any exceptions, as well as a detailed error description from JPF. Create a launch configuration for detecting possible deadlocks in the code, and run it in order to note the results.

Questions to answer

  • How would you have found the error in the program if you had not used JPF?
  • How does JPF find the deadlock? Use information from the trace printouts from the program as well as the description of how JPF works to justify your answer.

Concurrency testing 2: Race condition detection

The second concurrency test concerns race conditions. Race conditions appear when two threads want to modify the same resource, and the result of the program depends on the (random) order in which the threads are scheduled to run. We have a class race.Resource where two threads update a common value, and where the order in which they run determine the outcome. Apart from the general parameters, in this case we want to specify that a particular listener should be used, one that can detect race conditions.
+listener=gov.nasa.jpf.listener.PreciseRaceDetector
Questions to answer
  • How would you have found the error in the program if you had not used JPF?
  • What happens if you make the Updater.run or Pair.update methods synchronized? Why?

Symbolic execution 1: Test case generation with exceptions

JPF can use symbolic execution for exploring a number of different execution paths of a program at runtime. The documentation of the JPF module jpf-symbc describes how this works in general, and what parameters are of use. In this task, you will generate test cases for the class triangle.Main by using parameters to set up JPF for probing different execution paths in the program.
+vm.insn_factory.class=gov.nasa.jpf.symbc.SymbolicInstructionFactory
+listener=gov.nasa.jpf.symbc.SymbolicListener,gov.nasa.jpf.symbc.sequences.SymbolicSequenceListener
+symbolic.method=triangle.Triangle.getType(sym#sym#sym)
Questions to answer
  • What happens if you change the Triangle.getType method to not throw exceptions on invalid parameters but return TriangleType.NaT instead?
  • What test cases are generated if you replace the exception?
  • What happens if you change getType(sym#sym#sym) to getType(con#con#sym)?
  • What does the notation getType(con#con#sym) mean and what is the effect on the generated test cases? How do you think it could be used when probing the program for execution paths?

Symbolic execution 2: Test case generation with coverage analysis

Another listener that can be used is the gov.nasa.jpf.listener.CoverageAnalyzer that can provide information on the coverage that you will get from the test cases generated. In this excercise, you will use the method dataflow.Billing.calculateBill(int) as a target for your test case generation.
+vm.insn_factory.class=gov.nasa.jpf.symbc.SymbolicInstructionFactory
+listener=gov.nasa.jpf.symbc.SymbolicListener,gov.nasa.jpf.symbc.sequences.SymbolicSequenceListener,gov.nasa.jpf.listener.CoverageAnalyzer
+coverage.include=dataflow.Billing
+coverage.show_requirements=true
+symbolic.method=dataflow.Billing.calculateBill(sym)
Questions to answer
  • How does the SymbolicSequenceListener seem to select test case input values?
  • Do you get 100% statement coverage from the test cases? If not, why do you think that is so? Hint: consider the configuration parameters to the jpf.symbc package on how to select symbolic values for different datatypes.
  • Does the coverage indication provided by the CoverageAnalyzer seem correct to you? Justify your answer.

Last excercise: Experimentation

Look at the code examples in the directory sir_examples, used in software analysis research. These examples contain seeded bugs that a software analysis tool such as JPF should be able to find. The code examples are packaged in a standardized way suitable for experimentation, which means there is more information than merely the source code. You find the code in the directories called version.alt though.
  • Try to find the bugs in the code examples alarmclock and log4j2, and describe them. In the log4j2 example, there are two versions of the code, so you should be able to make out where the difference lies between the two version using the diff tool. In the alarmclock example, you should be able to explain the bug that JPF detects by inspecting the code that triggers the detected exception.

Reporting your results

See the general instructions for successfully completing the lab assignment. Note that you will have to upload the results on Gitlab before demonstrating to your assistant. Provide answers to the questions above, and describe the bugs in the last exercise as precisely as you can.

Page responsible: Lena Buffoni
Last updated: 2019-09-01