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Definition Classes: root

Definition Classes: root

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 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 seq

Definition Classes: fpcf

AnalysisScenario

ComputationSpecification

ComputationType

ContextNotAvailableException

EPK

EPS

EUBP

EUBPS

EagerComputation

ExplicitlyNamedProperty

FinalPropertyComputationResult

LBP

ProperPropertyComputationResult

PropertiesBoundType

Property

PropertyBounds

PropertyComputationResult

PropertyIsNotComputedByAnyAnalysis

PropertyIsNotDerivedByPreviouslyExecutedAnalysis

PropertyKey

PropertyKind

PropertyKindsConfiguration

PropertyMetaInformation

SimpleComputationSpecification

SinglePropertiesBoundType

SomeEPS

SomeFinalEP

SpecificationViolation

UBP

NoLBP

object NoLBP

Defines an extractor that matches EPKs and Interim properties where the latter only defines an upper bound, but does not define a lower bound.

For example, an analysis which declares that it can only handle lower bounds, but can't process EPSs which only define an upper bound, may still see EPS which define only the upper bound but can process them in the same way as an EPK; that is, it can basically ignore the upper bound information. The scheduler ensures that the analysis scenario is a valid one and no cyclic dependent computations may arise.

def continuation(eps : EPS) : ... = eps match {
  case FinalEP(...) => // Matches only final properties.
  case LBP(...)     => // Matches final  and interim properties which define a lower bound.
  case NoLBP(...)   => // Matches EPKs and EPS which just define an upper bound.
}

Source: EOptionP.scala

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def unapply[E <: Entity, P >: Null <: Property](eps: EOptionP[E, P]): Option[EOptionP[E, P]]
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General Design Decisions

Thread Safety

No `null` Values

No Typecasts for Collections

Assertions

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object NoLBP

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object NoLBP

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