wiki:devel/bytecode_factory

Bytecode Factories

Normally, a VM defines the semantics of it's programming language. In case of Java, the corresponding instruction set represents a multi-threaded stack machine, where values are kept on the heap, or inside of local- and/or operand- slots within stack frames. The effect of Java bytecode instructions with respect to heap, locals and operands are described in Sun's Java Virtual Machine Specification.

JPF is different. The JVM and it's associated constructs like ThreadInfo, ClassInfo, ElementInfo etc. provide all the necessary means to implement a normal Java interpreter, but JPF delegates the use of these means to the instructions. Every bytecode that gets executed by JPF is represented by a corresponding Instruction object, which normally gets instantiated during class load time. The Instruction classes of the standard execution mode can be found in package gov.nasa.jpf.jvm.bytecode.

When it comes to executing a bytecode, the JVM simply calls the execute() method of this Instruction instance. Whatever happens within these methods defines the execution semantics.

The trick is now that JPF uses a configurable abstract factory to choose and instantiate the Instruction classes. By providing your own concrete InstructionFactory, together with a set of related Instruction classes, you can change the execution semantics of Java.

Figure: Bytecode Factories

Usages

Why would it be useful to change the standard semantics? One reason is to extend normal semantics with additional checks. This is done in the [[ext:numeric|numeric]] JPF extension that overrides numeric bytecode classes with versions that check for over-/underflow and silent NaN propagation (among other things). A much more involved example is the [[ext:symbc|''symbc'' extension]], which implements a symbolic execution mode for Java, e.g. to automatically generate test cases based on the program structure of an application. It does so by overriding branch instructions, turning them into state space branches represented by their own choicegenerator ChoiceGenerators?, collecting the path conditions on the way, and feeding them to an external SAT solver.

Implementation

Since there is a large number of Java bytecodes, it would be tedious having to implement all 250+ Instruction classes in order to override just a couple of them. You can reduce the effort in three ways:

GenericInstructionFactory

Using the *GenericInstructionFactory as a base class for your InstructionFactory. This only requires you to specify an alternative package where your bytecode classes reside, together with the set of bytecodes that should be overridden. The resulting code can be quite short, as can be seen in the numeric extension example:

public class NumericInstructionFactory extends GenericInstructionFactory {
 
  // which bytecodes do we replace
  static final String[] BC_NAMES = {
    "DCMPG", "DCMPL",  "DADD", "DSUB", "DMUL", "DDIV",
    "FCMPG", "FCMPL",  "FADD", "FSUB", "FMUL", "FDIV",
                       "IADD", "ISUB", "IMUL", "IDIV",  "IINC", 
                       "LADD", "LSUB", "LMUL", "LDIV"   
  };
  
  // where do they reside
  protected static final String BC_PREFIX = "gov.nasa.jpf.numeric.bytecode.";
  
  // what classes should use them
  protected static final String[] DEFAULT_EXCLUDES = { "java.*", "javax.*" };
  
  public  NumericInstructionFactory (Config conf){    
    super(conf, BC_PREFIX, BC_NAMES, null, DEFAULT_EXCLUDES);
    
    NumericUtils.init(conf);
  }
}

Super Delegation

You can derive your overriding bytecode classes from the ones in gov.nasa.jpf.jvm.bytecode. If you just want to add some checks before or after performing the "normal" operation, you can use the standard Instruction classes as base classes, and call super.execute(..) from within your derived classes.

Attributes

As your execution semantics get more complex, you probably need to store and restore additional information that is associated with variables. JPF provides an automatically managed Attribute System for this purpose. You can attach objects to locals, operands and fields, and JPF takes care of propagating these attribute objects whenever it manipulates stackframes or heap objects.

Configuration

Configuring your bytecode factory just requires one JPF property, e.g.

vm.insn_factory.class = gov.nasa.jpf.numeric.NumericInstructionFactory

which can be either done from the command line or from within a *.jpf property file

Last modified 9 years ago Last modified on 08/27/2009 03:47:42 PM

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