Packages

  • package root
    Definition Classes
    root
  • package org
    Definition Classes
    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 - org.opalj.bi) that can be used to create arbitrary representations.
    • a library to create a one-to-one in-memory representation of Java bytecode (Bytecode Disassembler - org.opalj.da).
    • a library to convert this representation to Java class files (Bytecode Creator - org.opalj.bc).
    • a library to create a representation of Java bytecode that facilitates writing simple static analyses (Bytecode Representation - org.opalj.br).
    • a library to create a stackless, three-address code representation of Java bytecode that facilitates writing complex static analyses (Three Address Code - org.opalj.tac).
    • 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 (Dependencies Extraction - org.opalj.de) and to facilitate checking architecture definitions (Architecture Validation - org.opalj.av).
    • a library for the lightweight manipulation and creation of Java bytecode (Bytecode Assembler - org.opalj.ba).
    • a library for parsing Android packages (APK - org.opalj.apk).
    • libraries for writing static analyses using the interprocedural finite distributive subset (IFDS - org.opalj.ifds) and interprocedural distributive environment (IDE - org.opal.ide) algorithms.

    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 fpcf

    The fixpoint computations framework (fpcf) is a general framework to perform fixpoint computations of properties ordered by a lattice.

    The fixpoint computations framework (fpcf) is a general framework to perform fixpoint computations of properties ordered by a lattice. The framework in particular supports the development of static analyses.

    In this case, the fixpoint computations/static analyses are generally operating on the code and need to be executed until the computations have reached their (implicit) fixpoint. The fixpoint framework explicitly supports resolving cyclic dependencies/computations. A prime use case of the fixpoint framework are all those analyses that may interact with the results of other analyses.

    For example, an analysis that analyzes all field write accesses to determine if we can refine a field's type (for the purpose of the analysis) can (reuse) the information about the return types of methods, which however may depend on the refined field types.

    The framework is generic enough to facilitate the implementation of anytime algorithms.

    Definition Classes
    opalj
    Note

    This framework assumes that all data-structures (e.g., dependee lists and properties) that are passed to the framework are effectively immutable! (Effectively immutable means that a data structure is never updated after it was passed to the framework.)

    ,

    The dependency relation is as follows: “A depends on B” === “A is the depender, B is the dependee”. === “B is depended on by A”

    ,

    The very core of the framework is described in: Lattice Based Modularization of Static Analyses

  • package par
    Definition Classes
    fpcf
  • package scheduling
    Definition Classes
    fpcf
  • IndependentPhaseMergeScheduling
  • MaximumPhaseScheduling
  • MultiplePhaseScheduling
  • PhaseMergeScheduling
  • SchedulingStrategy
  • SinglePhaseScheduling
  • SmallestPhaseMergeScheduling
  • package seq
    Definition Classes
    fpcf
p

org.opalj.fpcf

scheduling

package scheduling

Ordering
  1. Alphabetic
Visibility
  1. Public
  2. Protected

Type Members

  1. abstract class MultiplePhaseScheduling extends SchedulingStrategy

    Base class for scheduling strategies that create multiple computation phases.

  2. abstract class PhaseMergeScheduling extends MultiplePhaseScheduling

    Base class for scheduling strategies that create multiple computation phases by merging multiple smaller independent phases into one.

  3. trait SchedulingStrategy extends AnyRef
  4. abstract class SinglePhaseScheduling extends SchedulingStrategy

Value Members

  1. object IndependentPhaseMergeScheduling extends PhaseMergeScheduling

    Merges independent batches to optimize parallelism.

  2. object MaximumPhaseScheduling extends MultiplePhaseScheduling

    Breaks down computations into as many phases as possible based on dependencies and computation types.

  3. object MultiplePhaseScheduling
  4. object SinglePhaseScheduling extends SinglePhaseScheduling

    Schedules all computations in a single batch without considering dependencies.

  5. object SmallestPhaseMergeScheduling extends PhaseMergeScheduling

    Merging batches based on the number of analyses to keep merged batches of similar sizes.

Ungrouped