DataFlowAnalysis

abstract val lattice: L

abstract def run(): Unit

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

def +(other: String): String

def ->[B](y: B): (DataFlowAnalysis[L], B)

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def backwardAnalysis(f: (P, L.Elem) ⇒ L.Elem): Unit

def clone(): AnyRef

def ensuring(cond: (DataFlowAnalysis[L]) ⇒ Boolean, msg: ⇒ Any): DataFlowAnalysis[L]

def ensuring(cond: (DataFlowAnalysis[L]) ⇒ Boolean): DataFlowAnalysis[L]

def ensuring(cond: Boolean, msg: ⇒ Any): DataFlowAnalysis[L]

def ensuring(cond: Boolean): DataFlowAnalysis[L]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def formatted(fmtstr: String): String

def forwardAnalysis(f: (P, L.Elem) ⇒ L.Elem): Unit

Implements forward dataflow analysis: the transfer function is applied when inputs to a Program point change, to obtain the new output value.

final def getClass(): Class[_]

def hashCode(): Int

val in: Map[P, L.Elem]

def init(f: ⇒ Unit): Unit

final def isInstanceOf[T0]: Boolean

var iterations: Int

the number of times we iterated before reaching a fixpoint.

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val out: Map[P, L.Elem]

var stat: Boolean

collect statistics?

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

val visited: HashSet[P]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

val worklist: Set[P]

def →[B](y: B): (DataFlowAnalysis[L], B)