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 analyses

    Defines commonly useful type aliases.

    Defines commonly useful type aliases.

    Definition Classes
    br
  • package cg
    Definition Classes
    analyses
  • Analysis
  • AnalysisApplication
  • AnalysisException
  • BasicMethodInfo
  • BasicReport
  • DeclaredMethods
  • DeclaredMethodsKey
  • FieldAccessInformation
  • FieldAccessInformationAnalysis
  • FieldAccessInformationKey
  • InconsistentProjectException
  • JavaProject
  • MethodAnalysisApplication
  • MethodDeclarationContext
  • MethodDeclarationContextOrdering
  • MethodInfo
  • ModuleDefinition
  • OneStepAnalysis
  • ProgressEvents
  • ProgressManagement
  • Project
  • ProjectAnalysisApplication
  • ProjectBasedAnalysis
  • ProjectIndex
  • ProjectIndexKey
  • ProjectInformationKey
  • ProjectLike
  • ReportableAnalysisResult
  • StringConstantsInformationKey
  • VirtualFormalParameter
  • VirtualFormalParameters
  • VirtualFormalParametersKey

trait ProgressManagement extends AnyRef

Enables the management of the progress of a long running computation. Typically a long running progress, such as an analysis, is expected to report progress every 250 to 2000 milliseconds. It should -- however -- check every ~100 milliseconds the interrupted status to enable a timely termination.

This trait defines a call-back interface that is implemented by some class that runs an analysis and which passes an instance of it to some analysis to report progress.

Source
ProgressManagement.scala
Note

Implementations of this class must be thread safe if the analysis is multi- threaded.

,

Implementations must handle the case where a step that was started later finishes earlier than a previous step. In other words, even if the last step has ended, that does not mean that the analysis as a whole has already finished. Instead an implementation has to track how many steps have ended to determine when the whole analysis has ended.

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Abstract Value Members

  1. abstract def isInterrupted(): Boolean

    This method is called by the analysis method to check whether the analysis should be aborted.

    This method is called by the analysis method to check whether the analysis should be aborted. The analysis will abort the computation if this method returns true.

  2. abstract def progress(step: Int, event: ProgressEvent, message: Option[String]): Unit

    This method is called by the analysis to report progress.

    This method is called by the analysis to report progress.

    An analysis is allowed to just report End events. However, if it reports Start events it must also report End events and it must use the same id to do so. This enables the correlation of the events. The analysis must never report more than one Start/End event per step id.

    If the analysis is interrupted it may either signal (as the very last event) a Killed event or an End event if the analysis completed normally.

    step

    The step/id of the event. The first event reported by the analysis has to use the number "1". The step id of the Killed event is "-1".

    message

    An optional message. Typically used in combination with Start events.

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  6. final def end(step: Int, message: Option[String]): Unit
  7. final def end(step: Int, message: String): Unit
  8. final def end(step: Int): Unit
  9. final def eq(arg0: AnyRef): Boolean
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  10. def equals(arg0: Any): Boolean
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  11. final def getClass(): Class[_]
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  13. final def isInstanceOf[T0]: Boolean
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  14. final def ne(arg0: AnyRef): Boolean
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  16. final def notifyAll(): Unit
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  17. final def start(step: Int, message: String): Unit
  18. final def step[T](step: Int, startMessage: String)(f: ⇒ (T, Option[String])): T

    A convenience method to execute one analysis step.

    A convenience method to execute one analysis step. If executing the step takes longer you have to call isInterrupted to check the interrupt status.

  19. final def synchronized[T0](arg0: ⇒ T0): T0
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  20. def toString(): String
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  21. final def wait(arg0: Long, arg1: Int): Unit
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  22. final def wait(arg0: Long): Unit
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  23. final def wait(): Unit
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  1. def finalize(): Unit
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