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) 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 br

    In this representation of Java bytecode references to a Java class file's constant pool and to attributes are replaced by direct references to the corresponding constant pool entries.

    In this representation of Java bytecode references to a Java class file's constant pool and to attributes are replaced by direct references to the corresponding constant pool entries. This facilitates developing analyses and fosters comprehension.

    Based on the fact that indirect references to constant pool entries are resolved and replaced by direct references this representation is called the resolved representation.

    This representation of Java bytecode is considered as OPAL's standard representation for writing Scala based analyses. This representation is engineered such that it facilitates writing analyses that use pattern matching.

    Definition Classes
    opalj
  • package fpcf
    Definition Classes
    br
  • package analyses
    Definition Classes
    fpcf
  • package properties
    Definition Classes
    fpcf
  • BasicFPCFEagerAnalysisScheduler
  • BasicFPCFLazyAnalysisScheduler
  • BasicFPCFTransformerScheduler
  • BasicFPCFTriggeredAnalysisScheduler
  • DefaultFPCFAnalysis
  • FPCFAnalysesManager
  • FPCFAnalysesManagerKey
  • FPCFAnalysesRegistry
  • FPCFAnalysis
  • FPCFAnalysisScheduler
  • FPCFEagerAnalysisScheduler
  • FPCFLazyAnalysisScheduler
  • FPCFLazyLikeAnalysisScheduler
  • FPCFTransformerScheduler
  • FPCFTriggeredAnalysisScheduler
  • PropertyStoreKey

class FPCFAnalysesManager extends AnyRef

Enables the execution of a set of analyses.

To get an instance use the respective FPCFAnalysesManagerKey.

Source
FPCFAnalysesManager.scala
Linear Supertypes
AnyRef, Any
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Inherited
  1. FPCFAnalysesManager
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Visibility
  1. Public
  2. Protected

Value Members

  1. def executedSchedules: List[Schedule[FPCFAnalysis]]

    Returns the executed schedules.

    Returns the executed schedules. The head is the latest executed schedule.

  2. val project: SomeProject
  3. final def runAll(analyses: Iterable[ComputationSpecification[FPCFAnalysis]], afterPhaseScheduling: (List[ComputationSpecification[FPCFAnalysis]]) => Unit = _ => ()): (PropertyStore, List[(ComputationSpecification[FPCFAnalysis], FPCFAnalysis)])
  4. final def runAll(analyses: ComputationSpecification[FPCFAnalysis]*): (PropertyStore, List[(ComputationSpecification[FPCFAnalysis], FPCFAnalysis)])