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 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.

    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. Furthermore, the concrete data-structure is always considered an implementation detail and may change at any time.

    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 ai

    Implementation of an abstract interpretation (ai) framework – also referred to as OPAL.

    Implementation of an abstract interpretation (ai) framework – also referred to as OPAL.

    Please note, that OPAL/the abstract interpreter just refers to the classes and traits defined in this package (ai). The classes and traits defined in the sub-packages (in particular in domain) are not considered to be part of the core of OPAL/the abstract interpreter.

    Definition Classes
    opalj
    Note

    This framework assumes that the analyzed bytecode is valid; i.e., the JVM's bytecode verifier would be able to verify the code. Furthermore, load-time errors (e.g., LinkageErrors) are – by default – completely ignored to facilitate the analysis of parts of a project. In general, if the presented bytecode is not valid, the result is undefined (i.e., OPAL may report meaningless results, crash or run indefinitely).

    See also

    org.opalj.ai.Domain - The core interface between the abstract interpretation framework and the abstract domain that is responsible for performing the abstract computations.

    org.opalj.ai.AI - Implements the abstract interpreter that processes a methods code and uses an analysis-specific domain to perform the abstract computations.

  • package project
    Definition Classes
    ai
  • AIProject
  • OptionalReport
t

org.opalj.ai.project

AIProject

trait AIProject[Source, D <: Domain with OptionalReport] extends AnyRef

Template class for analyzing complete Java projects that use the abstract interpreter.

This trait is intended to be used in combination with the Analysis and the AnalysisExecutor traits to easily create a readily executable analysis (see the Demos project for examples).

Source
AIProject.scala
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Abstract Value Members

  1. abstract def ai: AI[D]

    Returns the abstract interpreter that should be used for performing the abstract interpretations.

  2. abstract def domain(project: Project[Source], method: Method): D

    Returns the (initial) domain object that will be used to analyze an entry point.

    Returns the (initial) domain object that will be used to analyze an entry point.

    The analysis of all entry points may happen concurrently unless analyzeInParallel is false.

  3. abstract def entryPoints(project: Project[Source]): Iterable[Method]

    A project's entry points.

    A project's entry points.

    In case of a very simple command-line application, the set of entry points may just consist of the application's main method.

    If, for example, a desktop application with a GUI is to be analyzed, the entry points are usually the application's main method and all those listeners that react on system-level events (mouse move events, keyboard events etc.)

    In case of a framework, the set of entry points typically encompasses all non-private constructors, all non-private static methods and all static initializers. Additionally, listeners for system-level events are also entry points.

    returns

    All methods that are potential entry points.

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  4. def analyze(project: Project[Source], parameters: Seq[String]): ReportableAnalysisResult

    Analyzes the given project by first determining the entry points of the analysis and then starting an independent analysis for each entry point using its own domain.

    Analyzes the given project by first determining the entry points of the analysis and then starting an independent analysis for each entry point using its own domain.

    Note

    This method is intended to be overridden by subtraits that need to get hold on the specified analysis parameters. In this case (in the subtrait) it is recommended to first analyze the parameters and afterwards to call this method using super.analyze(...).

  5. val analyzeInParallel: Boolean

    If true (default) all entry points will be analyzed in parallel.

    If true (default) all entry points will be analyzed in parallel.

    Needs to be overridden by subclasses if the entry points should be analyzed sequentially.

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