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    root
  • package opalj

    OPAL is a Scala-based framework for the static analysis, manipulation and creation of Java bytecode.

    OPAL is a Scala-based framework for the static analysis, manipulation and creation of Java bytecode. OPAL is designed with performance, scalability and adaptability in mind.

    Its main components are:

    • a library (Common) which provides generally useful data-structures and algorithms for static analyses.
    • a framework for implementing lattice based static analyses (Static Analysis Infrastructure)
    • a framework for parsing Java bytecode (Bytecode Infrastructure) that can be used to create arbitrary representations.
    • a library to create a one-to-one in-memory representation of Java bytecode (Bytecode Disassembler).
    • a library to create a representation of Java bytecode that facilitates writing simple static analyses (Bytecode Representation - org.opalj.br).
    • a scalable, easily customizable framework for the abstract interpretation of Java bytecode (Abstract Interpretation Framework - org.opalj.ai).
    • a library to extract dependencies between code elements and to facilitate checking architecture definitions.
    • a library for the lightweight manipulation and creation of Java bytecode (Bytecode Assembler).

    General Design Decisions

    Thread Safety

    Unless explicitly noted, OPAL is thread safe. I.e., the classes defined by OPAL can be considered to be thread safe unless otherwise stated. (For example, it is possible to read and process class files concurrently without explicit synchronization on the client side.)

    No null Values

    Unless explicitly noted, OPAL does not null values I.e., fields that are accessible will never contain null values and methods will never return null. If a method accepts null as a value for a parameter or returns a null value it is always explicitly documented. In general, the behavior of methods that are passed null values is undefined unless explicitly documented.

    No Typecasts for Collections

    For efficiency reasons, OPAL sometimes uses mutable data-structures internally. After construction time, these data-structures are generally represented using their generic interfaces (e.g., scala.collection.{Set,Map}). However, a downcast (e.g., to add/remove elements) is always forbidden as it would effectively prevent thread-safety.

    Assertions

    OPAL makes heavy use of Scala's Assertion Facility to facilitate writing correct code. Hence, for production builds (after thorough testing(!)) it is highly recommend to build OPAL again using -Xdisable-assertions.

    Definition Classes
    org
  • package graphs

    This package defines graph algorithms as well as factory methods to describe and compute graphs and trees.

    This package defines graph algorithms as well as factory methods to describe and compute graphs and trees.

    This package supports the following types of graphs:

    1. graphs based on explicitly connected nodes (org.opalj.graphs.Node),
    2. graphs where the relationship between the nodes are encoded externally (org.opalj.graphs.Graph).
    Definition Classes
    opalj
  • AbstractDominatorTree
  • AbstractGraph
  • ControlDependencies
  • DefaultMutableMode
  • DefaultMutableNode
  • DominanceFrontiers
  • DominatorTree
  • Graph
  • MutableNode
  • MutableNodeLike
  • Node
  • PostDominatorTree
  • UnidirectionalGraph
  • VirtualUnidirectionalGraph

object DominatorTree

Factory to compute DominatorTrees.

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  4. def apply[D <: AbstractDominatorTree](startNode: Int, startNodeHasPredecessors: Boolean, foreachSuccessorOf: (Int) ⇒ ((Int) ⇒ Unit) ⇒ Unit, foreachPredecessorOf: (Int) ⇒ ((Int) ⇒ Unit) ⇒ Unit, maxNode: Int, dominatorTreeFactory: (Int, Boolean, (Int) ⇒ ((Int) ⇒ Unit) ⇒ Unit, Array[Int]) ⇒ D): D

    Computes the immediate dominators for each node of a given graph.

    Computes the immediate dominators for each node of a given graph. Each node of the graph is identified using a unique int value (e.g. the pc of an instruction) in the range [0..maxNode], although not all ids need to be used.

    startNode

    The id of the root node of the graph. (Often pc="0" for the CFG computed for some method; sometimes the id of an artificial start node that was created when computing the dominator tree).

    startNodeHasPredecessors

    If true an artificial start node with the id maxNode+1 will be created and added to the graph.

    foreachSuccessorOf

    A function that given a node subsequently executes the given function for each direct successor of the given node.

    foreachPredecessorOf

    A function that - given a node - executes the given function for each direct predecessor. The signature of a function that can directly be passed as a parameter is:

    def foreachPredecessorOf(pc: PC)(f: PC ⇒ Unit): Unit
    maxNode

    The largest unique int id that identifies a node. (E.g., in case of the analysis of some code it is typically equivalent to the length of the code-1.)

    returns

    The computed dominator tree.

    Note

    This is an implementation of the "fast dominators" algorithm presented by 

             T. Lengauaer and R. Tarjan in
         A Fast Algorithm for Finding Dominators in a Flowgraph
         ACM Transactions on Programming Languages and Systems (TOPLAS) 1.1 (1979): 121-141
    This implementation does not use non-tailrecursive methods and hence also handles very large degenerated graphs (e.g., a graph which consists of a a very, very long single path.).

  5. def apply(startNode: Int, startNodeHasPredecessors: Boolean, foreachSuccessorOf: (Int) ⇒ ((Int) ⇒ Unit) ⇒ Unit, foreachPredecessorOf: (Int) ⇒ ((Int) ⇒ Unit) ⇒ Unit, maxNode: Int): DominatorTree

    Convenience factory method for dominator trees; see org.opalj.graphs.DominatorTree$.apply[D<:org\.opalj\.graphs\.AbstractDominatorTree]* for details.

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