NormalLinearizer

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

def +(other: String): String

def ->[B](y: B): (ICodes.NormalLinearizer, B)

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

def add(bs: List[ICodes.BasicBlock]): Unit

def add(b: ICodes.BasicBlock): Unit

Prepend b to the list, if not already scheduled.

final def asInstanceOf[T0]: T0

var blocks: List[ICodes.BasicBlock]

def clone(): AnyRef

def dequeue: Elem

Remove and return the first element to be processed from the worklist.

def ensuring(cond: (ICodes.NormalLinearizer) ⇒ Boolean, msg: ⇒ Any): ICodes.NormalLinearizer

def ensuring(cond: (ICodes.NormalLinearizer) ⇒ Boolean): ICodes.NormalLinearizer

def ensuring(cond: Boolean, msg: ⇒ Any): ICodes.NormalLinearizer

def ensuring(cond: Boolean): ICodes.NormalLinearizer

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def formatted(fmtstr: String): String

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def linearize(startBlock: ICodes.BasicBlock): List[ICodes.BasicBlock]

Linearize another subtree and append it to the existing blocks.

def linearize(m: ICodes.IMethod): List[ICodes.BasicBlock]

def linearizeAt(m: ICodes.IMethod, start: ICodes.BasicBlock): List[ICodes.BasicBlock]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def processElement(b: ICodes.BasicBlock): Unit

Process the current element from the worklist.

def run(initWorklist: ⇒ Unit): Unit

Run the iterative algorithm until the worklist remains empty.

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

val worklist: WList

def →[B](y: B): (ICodes.NormalLinearizer, B)

val self: Any

val self: Any

def x: ICodes.NormalLinearizer

def x: ICodes.NormalLinearizer