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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 PostDominatorTree

Factory for post dominator trees.

Source
PostDominatorTree.scala
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  4. def apply(uniqueExitNode: Option[Int], isExitNode: (Int) => Boolean, additionalExitNodes: IntTrieSet, foreachExitNode: ((Int) => Unit) => Unit, foreachSuccessorOf: (Int) => ((Int) => Unit) => Unit, foreachPredecessorOf: (Int) => ((Int) => Unit) => Unit, maxNode: Int): PostDominatorTree

    Computes the post dominator tree for the given control flow graph.

    Computes the post dominator tree for the given control flow graph. (The reverse control flow graph will computed on demand by this method.) If necessary, an artificial start node will be created to ensure that we have a unique start node for the post dominator tree; if created the node will have the id = (maxNodeId+1); additionally, all edges are automatically reversed.

    If this post-dominator tree is used to compute control-dependence information, the control-dependence information is generally non-termination insensitive; i.e., conceptually every loop is expected to eventually terminate. Hence, an instruction following the loop will not depend on the if related to evaluating the loop condition. However, non-handled exceptions (i.e., if we have multiple exit nodes), may destroy this illusion! For details see: 

    A New Foundation for Control Dependence and Slicing for Modern Program Structures
2007, Journal Version appeared in ACM TOPLAS

    uniqueExitNode

    true if and only if the underlying CFG has a a unique exit node. (This property is independent of the additionalExitNodes property which is not a statement about the underlying CFG, but a directive how to compute the post-dominator tree.)

    isExitNode

    A function that returns true if the given node – in the underlying (control-flow) graph – is an exit node; that is the node has no successors.

    foreachExitNode

    A function f that takes a function g with an int parameter which identifies a node and which executes g for each exit node. Note that _all nodes_ except those belonging to those transitively reachable from a start node of an infinite loop have to be reachable from the exit nodes; otherwise the PostDominatorTree will be a forest and will be generally useless.

    maxNode

    The largest id used by the underlying (control-flow) graph; required to assign the virtual start node of the pdt - if required - a unique id.

    Example:

    1. Computing the post dominator tree:

      scala>//Graph: 0 -> 1->E;  1 -> 2->E
scala>def isExitNode(i: Int) = i == 1 || i == 2
isExitNode: (i: Int)Boolean

 scala>def foreachExitNode(f: Int => Unit) = { f(1); f(2) }
foreachExitNode: (f: Int => Unit)Unit

scala>def foreachPredecessorOf(i: Int)(f: Int => Unit) = i match {
     |    case 0 =>
     |    case 1 => f(0)
     |    case 2 => f(1)
     |}
foreachPredecessorOf: (i: Int)(f: Int => Unit)Unit
scala>def foreachSuccessorOf(i: Int)(f: Int => Unit) = i match {
      |    case 0 => f(1)
      |    case 1 => f(2)
      |    case 2 =>
      |}
foreachSuccessorOf: (i: Int)(f: Int => Unit)Unit
scala>val pdt = org.opalj.graphs.PostDominatorTree.apply(
     |    uniqueExitNode = None,
     |    isExitNode,
     |    org.opalj.collection.immutable.IntTrieSet.empty,
     |    foreachExitNode,
     |    foreachSuccessorOf,
     |    foreachPredecessorOf,
     |    2
     |)
pdt: org.opalj.graphs.PostDominatorTree = org.opalj.graphs.PostDominatorTree@3a82ac80
scala>pdt.toDot()
scala>org.opalj.io.writeAndOpen(pdt.toDot(i => true),"PDT",".gv")
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